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The Data Science Course Complete Data Science Bootcamp 2025 Dec

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English

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9.2 GB

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9A03EAE6885C6EACA8F516880C02705743F8EACA

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notimmune

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May 7, 2025, 9:30 a.m.

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| (Last updated: May 7, 2025, 9:31 a.m.)

File	Size
01. A Practical Example What You Will Learn in This Course.mp4	10.8 MB
01. A Practical Example What You Will Learn in This Course.vtt	6.8 KB
02. What Does the Course Cover.mp4	9.6 MB
02. What Does the Course Cover.vtt	5.4 KB
03. Download All Resources and Important FAQ.html	21.3 KB
03. FAQ-The-Data-Science-Course.pdf	306.1 KB
01. Data Science and Business Buzzwords Why are there so Many.mp4	15.6 MB
01. Data Science and Business Buzzwords Why are there so Many.vtt	7.4 KB
02. What is the difference between Analysis and Analytics.mp4	11.2 MB
02. What is the difference between Analysis and Analytics.vtt	5.1 KB
03. Business Analytics, Data Analytics, and Data Science An Introduction.mp4	14.6 MB
03. Business Analytics, Data Analytics, and Data Science An Introduction.vtt	9.6 KB
04. Continuing with BI, ML, and AI.mp4	47.6 MB
04. Continuing with BI, ML, and AI.vtt	13.1 KB
05. Traditional AI vs. Generative AI.mp4	24.5 MB
05. Traditional AI vs. Generative AI.vtt	6.9 KB
06. More Examples of Generative AI.mp4	30.5 MB
06. More Examples of Generative AI.vtt	6.9 KB
07. A Breakdown of our Data Science Infographic.mp4	45.4 MB
07. A Breakdown of our Data Science Infographic.vtt	5.1 KB
03. 365-DataScience-Diagram.pdf	323.1 KB
04. 365-DataScience-Diagram.pdf	323.1 KB
04. 365-DataScience.png	6.9 MB
07. 365-DataScience.png	6.9 MB
01. Applying Traditional Data, Big Data, BI, Traditional Data Science and ML.mp4	83.5 MB
01. Applying Traditional Data, Big Data, BI, Traditional Data Science and ML.vtt	9.2 KB
01. The Reason Behind These Disciplines.mp4	46.8 MB
01. The Reason Behind These Disciplines.vtt	6.5 KB
01. Techniques for Working with Traditional Data.mp4	107.2 MB
01. Techniques for Working with Traditional Data.vtt	11.0 KB
02. Real Life Examples of Traditional Data.mp4	18.4 MB
02. Real Life Examples of Traditional Data.vtt	2.3 KB
03. Techniques for Working with Big Data.mp4	62.1 MB
03. Techniques for Working with Big Data.vtt	5.8 KB
04. Real Life Examples of Big Data.mp4	13.0 MB
04. Real Life Examples of Big Data.vtt	1.9 KB
05. Business Intelligence (BI) Techniques.mp4	52.9 MB
05. Business Intelligence (BI) Techniques.vtt	8.8 KB
06. Real Life Examples of Business Intelligence (BI).mp4	24.6 MB
06. Real Life Examples of Business Intelligence (BI).vtt	2.3 KB
07. Techniques for Working with Traditional Methods.mp4	76.0 MB
07. Techniques for Working with Traditional Methods.vtt	11.5 KB
08. Real Life Examples of Traditional Methods.mp4	36.7 MB
08. Real Life Examples of Traditional Methods.vtt	5.4 KB
09. Machine Learning (ML) Techniques.mp4	49.4 MB
09. Machine Learning (ML) Techniques.vtt	9.3 KB
10. Types of Machine Learning.mp4	69.5 MB
10. Types of Machine Learning.vtt	10.9 KB
11. Evolution and Latest Trends of Machine Learning (ML).mp4	27.3 MB
11. Evolution and Latest Trends of Machine Learning (ML).vtt	7.8 KB
12. Real Life Examples of Machine Learning (ML).mp4	27.7 MB
12. Real Life Examples of Machine Learning (ML).vtt	3.0 KB
01. Necessary Programming Languages and Software Used in Data Science.mp4	82.4 MB
01. Necessary Programming Languages and Software Used in Data Science.vtt	8.0 KB
01. Finding the Job - What to Expect and What to Look for.mp4	40.0 MB
01. Finding the Job - What to Expect and What to Look for.vtt	4.7 KB
01. Debunking Common Misconceptions.mp4	58.9 MB
01. Debunking Common Misconceptions.vtt	5.5 KB
01. The Basic Probability Formula.mp4	29.4 MB
01. The Basic Probability Formula.vtt	9.0 KB
02. Computing Expected Values.mp4	45.7 MB
02. Computing Expected Values.vtt	7.0 KB
03. Frequency.mp4	37.4 MB
03. Frequency.vtt	6.9 KB
04. Events and Their Complements.mp4	25.8 MB
04. Events and Their Complements.vtt	7.1 KB
01. Course-Notes-Basic-Probability.pdf	371.1 KB
01. Fundamentals of Combinatorics.mp4	5.9 MB
01. Fundamentals of Combinatorics.vtt	1.5 KB
02. Permutations and How to Use Them.mp4	17.5 MB
02. Permutations and How to Use Them.vtt	4.4 KB
03. Simple Operations with Factorials.mp4	10.5 MB
03. Simple Operations with Factorials.vtt	3.4 KB
04. Solving Variations with Repetition.mp4	13.9 MB
04. Solving Variations with Repetition.vtt	3.8 KB
05. Solving Variations without Repetition.mp4	18.3 MB
05. Solving Variations without Repetition.vtt	4.9 KB
06. Solving Combinations.mp4	23.6 MB
06. Solving Combinations.vtt	6.0 KB
07. Symmetry of Combinations.mp4	13.7 MB
07. Symmetry of Combinations.vtt	4.5 KB
08. Solving Combinations with Separate Sample Spaces.mp4	20.3 MB
08. Solving Combinations with Separate Sample Spaces.vtt	4.1 KB
09. Combinatorics in Real-Life The Lottery.mp4	16.4 MB
09. Combinatorics in Real-Life The Lottery.vtt	4.2 KB
10. A Recap of Combinatorics.mp4	12.1 MB
10. A Recap of Combinatorics.vtt	3.8 KB
11. A Practical Example of Combinatorics.mp4	80.7 MB
11. A Practical Example of Combinatorics.vtt	15.2 KB
01. Course-Notes-Combinatorics.pdf	226.1 KB
06. Combinations-With-Repetition.pdf	207.4 KB
07. Symmetry-Explained.pdf	85.0 KB
11. Additional-Exercises-Combinatorics-Solutions.pdf	245.7 KB
11. Additional-Exercises-Combinatorics.pdf	106.6 KB
01. Sets and Events.mp4	17.7 MB
01. Sets and Events.vtt	5.5 KB
02. Ways Sets Can Interact.mp4	11.3 MB
02. Ways Sets Can Interact.vtt	4.6 KB
03. Intersection of Sets.mp4	11.0 MB
03. Intersection of Sets.vtt	2.6 KB
04. Union of Sets.mp4	24.2 MB
04. Union of Sets.vtt	6.3 KB
05. Mutually Exclusive Sets.mp4	10.6 MB
05. Mutually Exclusive Sets.vtt	2.8 KB
06. Dependence and Independence of Sets.mp4	14.9 MB
06. Dependence and Independence of Sets.vtt	3.5 KB
07. The Conditional Probability Formula.mp4	20.1 MB
07. The Conditional Probability Formula.vtt	5.9 KB
08. The Law of Total Probability.mp4	14.2 MB
08. The Law of Total Probability.vtt	3.9 KB
09. The Additive Rule.mp4	11.1 MB
09. The Additive Rule.vtt	2.7 KB
10. The Multiplication Law.mp4	20.2 MB
10. The Multiplication Law.vtt	4.7 KB
11. Bayes' Law.mp4	21.3 MB
11. Bayes' Law.vtt	7.7 KB
12. A Practical Example of Bayesian Inference.mp4	139.2 MB
12. A Practical Example of Bayesian Inference.vtt	20.1 KB
01. Course-Notes-Bayesian-Inference.pdf	386.0 KB
12. Bayesian-Homework-Solutions.pdf	30.4 KB
12. Bayesian-Homework.pdf	27.3 KB
12. CDS-2017-2018-Hamilton.pdf	845.3 KB
01. Fundamentals of Probability Distributions.mp4	19.4 MB
01. Fundamentals of Probability Distributions.vtt	8.4 KB
02. Types of Probability Distributions.mp4	35.6 MB
02. Types of Probability Distributions.vtt	10.4 KB
03. Characteristics of Discrete Distributions.mp4	9.4 MB
03. Characteristics of Discrete Distributions.vtt	2.6 KB
04. Discrete Distributions The Uniform Distribution.mp4	10.3 MB
04. Discrete Distributions The Uniform Distribution.vtt	2.9 KB
05. Discrete Distributions The Bernoulli Distribution.mp4	15.1 MB
05. Discrete Distributions The Bernoulli Distribution.vtt	5.2 KB
06. Discrete Distributions The Binomial Distribution.mp4	30.6 MB
06. Discrete Distributions The Binomial Distribution.vtt	8.8 KB
07. Discrete Distributions The Poisson Distribution.mp4	23.9 MB
07. Discrete Distributions The Poisson Distribution.vtt	7.2 KB
08. Characteristics of Continuous Distributions.mp4	21.3 MB
08. Characteristics of Continuous Distributions.vtt	9.2 KB
09. Continuous Distributions The Normal Distribution.mp4	20.0 MB
09. Continuous Distributions The Normal Distribution.vtt	5.1 KB
10. Continuous Distributions The Standard Normal Distribution.mp4	21.1 MB
10. Continuous Distributions The Standard Normal Distribution.vtt	5.7 KB
11. Continuous Distributions The Students' T Distribution.mp4	9.2 MB
11. Continuous Distributions The Students' T Distribution.vtt	3.2 KB
12. Continuous Distributions The Chi-Squared Distribution.mp4	11.2 MB
12. Continuous Distributions The Chi-Squared Distribution.vtt	3.0 KB
13. Continuous Distributions The Exponential Distribution.mp4	16.0 MB
13. Continuous Distributions The Exponential Distribution.vtt	4.5 KB
14. Continuous Distributions The Logistic Distribution.mp4	16.2 MB
14. Continuous Distributions The Logistic Distribution.vtt	5.4 KB
15. A Practical Example of Probability Distributions.mp4	138.3 MB
15. A Practical Example of Probability Distributions.vtt	21.1 KB
01. Course-Notes-Probability-Distributions.pdf	463.9 KB
07. Poisson-Expected-Value-and-Variance.pdf	146.0 KB
08. Solving-Integrals.pdf	343.9 KB
09. Normal-Distribution-Exp-and-Var.pdf	144.1 KB
15. Customers-Membership-post.xlsx	15.6 KB
15. Customers-Membership.xlsx	9.7 KB
15. Daily-Views-post.xlsx	20.2 KB
15. Daily-Views.xlsx	9.5 KB
15. FIFA19-post.csv	8.6 MB
15. FIFA19.csv	8.6 MB
01. Probability in Finance.mp4	40.3 MB
01. Probability in Finance.vtt	10.1 KB
02. Probability in Statistics.mp4	31.6 MB
02. Probability in Statistics.vtt	9.1 KB
03. Probability in Data Science.mp4	14.2 MB
03. Probability in Data Science.vtt	7.1 KB
01. Probability-in-Finance-Homework.pdf	110.7 KB
01. Probability-in-Finance-Solutions.pdf	184.5 KB
03. Probability-Cheat-Sheet.pdf	320.3 KB
01. Population and Sample.mp4	35.1 MB
01. Population and Sample.vtt	5.8 KB
01. Course-notes-descriptive-statistics.pdf	482.2 KB
01. Statistics-Glossary.xlsx	20.3 KB
01. Types of Data.mp4	43.2 MB
01. Types of Data.vtt	5.8 KB
02. Levels of Measurement.mp4	32.2 MB
02. Levels of Measurement.vtt	4.8 KB
03. Categorical Variables - Visualization Techniques.mp4	27.5 MB
03. Categorical Variables - Visualization Techniques.vtt	6.7 KB
04. Categorical Variables Exercise.html	81 bytes
05. Numerical Variables - Frequency Distribution Table.mp4	17.7 MB
05. Numerical Variables - Frequency Distribution Table.vtt	4.5 KB
06. Numerical Variables Exercise.html	81 bytes
07. The Histogram.mp4	9.6 MB
07. The Histogram.vtt	3.4 KB
08. Histogram Exercise.html	81 bytes
09. Cross Tables and Scatter Plots.mp4	19.7 MB
09. Cross Tables and Scatter Plots.vtt	6.9 KB
10. Cross Tables and Scatter Plots Exercise.html	81 bytes
11. Mean, median and mode.mp4	24.5 MB
11. Mean, median and mode.vtt	6.0 KB
12. Mean, Median and Mode Exercise.html	81 bytes
13. Skewness.mp4	13.3 MB
13. Skewness.vtt	3.7 KB
14. Skewness Exercise.html	81 bytes
15. Variance.mp4	23.5 MB
15. Variance.vtt	8.2 KB
16. Variance Exercise.html	522 bytes
17. Standard Deviation and Coefficient of Variation.mp4	20.1 MB
17. Standard Deviation and Coefficient of Variation.vtt	6.3 KB
18. Standard Deviation and Coefficient of Variation Exercise.html	81 bytes
19. Covariance.mp4	18.4 MB
19. Covariance.vtt	5.1 KB
20. Covariance Exercise.html	81 bytes
21. Correlation Coefficient.mp4	19.3 MB
21. Correlation Coefficient.vtt	5.0 KB
22. Correlation Coefficient Exercise.html	81 bytes
01. Course-notes-descriptive-statistics.pdf	482.2 KB
01. Glossary.xlsx	20.0 KB
03. 2.3.Categorical-variables.Visualization-techniques-lesson.xlsx	30.8 KB
04. 2.3.Categorical-variables.Visualization-techniques-exercise-solution.xlsx	41.1 KB
04. 2.3.Categorical-variables.Visualization-techniques-exercise.xlsx	15.2 KB
04. Statistics-PDF-with-Excel-Solutions-that-dont-visualize-properly.pdf	289.1 KB
05. 2.4.Numerical-variables.Frequency-distribution-table-lesson.xlsx	11.4 KB
06. 2.4.Numerical-variables.Frequency-distribution-table-exercise-solution.xlsx	13.2 KB
07. 2.5.The-Histogram-lesson.xlsx	18.6 KB
08. 2.5.The-Histogram-exercise-solution.xlsx	17.1 KB
08. 2.5.The-Histogram-exercise.xlsx	15.5 KB
08. Statistics-PDF-with-Excel-Solutions-that-dont-visualize-properly.pdf	289.1 KB
09. 2.6.Cross-table-and-scatter-plot.xlsx	26.1 KB
10. 2.6.Cross-table-and-scatter-plot-exercise-solution.xlsx	40.4 KB
10. 2.6.Cross-table-and-scatter-plot-exercise.xlsx	16.3 KB
11. 2.7.Mean-median-and-mode-lesson.xlsx	10.5 KB
12. 2.7.Mean-median-and-mode-exercise-solution.xlsx	11.4 KB
12. 2.7.Mean-median-and-mode-exercise.xlsx	10.9 KB
13. 2.8.Skewness-lesson.xlsx	34.6 KB
14. 2.8.Skewness-exercise-solution.xlsx	19.8 KB
14. 2.8.Skewness-exercise.xlsx	9.5 KB
15. 2.9.Variance-lesson.xlsx	10.1 KB
16. 2.9.Variance-exercise-solution.xlsx	11.1 KB
16. 2.9.Variance-exercise.xlsx	10.8 KB
17. 2.10.Standard-deviation-and-coefficient-of-variation-lesson.xlsx	11.0 KB
18. 2.10.Standard-deviation-and-coefficient-of-variation-exercise-solution.xlsx	12.6 KB
18. 2.10.Standard-deviation-and-coefficient-of-variation-exercise.xlsx	11.6 KB
19. 2.11.Covariance-lesson.xlsx	24.9 KB
20. 2.11.Covariance-exercise-solution.xlsx	29.5 KB
20. 2.11.Covariance-exercise.xlsx	20.2 KB
22. 2.12.Correlation-exercise-solution.xlsx	29.5 KB
22. 2.12.Correlation-exercise.xlsx	29.3 KB
01. Practical Example Descriptive Statistics.mp4	130.5 MB
01. Practical Example Descriptive Statistics.vtt	21.0 KB
02. Practical Example Descriptive Statistics Exercise.html	81 bytes
01. 2.13.Practical-example.Descriptive-statistics-lesson.xlsx	146.5 KB
02. 2.13.Practical-example.Descriptive-statistics-exercise-solution.xlsx	146.4 KB
02. 2.13.Practical-example.Descriptive-statistics-exercise.xlsx	120.3 KB
01. Introduction.mp4	3.1 MB
01. Introduction.vtt	1.7 KB
02. What is a Distribution.mp4	17.2 MB
02. What is a Distribution.vtt	5.9 KB
03. The Normal Distribution.mp4	13.1 MB
03. The Normal Distribution.vtt	5.2 KB
04. The Standard Normal Distribution.mp4	8.6 MB
04. The Standard Normal Distribution.vtt	4.0 KB
05. The Standard Normal Distribution Exercise.html	81 bytes
06. Central Limit Theorem.mp4	23.2 MB
06. Central Limit Theorem.vtt	5.6 KB
07. Standard error.mp4	13.5 MB
07. Standard error.vtt	2.1 KB
08. Estimators and Estimates.mp4	27.7 MB
08. Estimators and Estimates.vtt	4.0 KB
01. Course-notes-inferential-statistics.pdf	382.3 KB
02. 3.2.What-is-a-distribution-lesson.xlsx	19.5 KB
02. Course-notes-inferential-statistics.pdf	382.3 KB
04. 3.4.Standard-normal-distribution-lesson.xlsx	10.4 KB
05. 3.4.Standard-normal-distribution-exercise-solution.xlsx	24.0 KB
05. 3.4.Standard-normal-distribution-exercise.xlsx	12.0 KB
01. What are Confidence Intervals.mp4	28.6 MB
01. What are Confidence Intervals.vtt	3.2 KB
02. Confidence Intervals; Population Variance Known; Z-score.mp4	52.2 MB
02. Confidence Intervals; Population Variance Known; Z-score.vtt	9.6 KB
03. Confidence Intervals; Population Variance Known; Z-score; Exercise.html	81 bytes
04. Confidence Interval Clarifications.mp4	18.9 MB
04. Confidence Interval Clarifications.vtt	5.6 KB
05. Student's T Distribution.mp4	13.7 MB
05. Student's T Distribution.vtt	4.6 KB
06. Confidence Intervals; Population Variance Unknown; T-score.mp4	13.7 MB
06. Confidence Intervals; Population Variance Unknown; T-score.vtt	5.4 KB
07. Confidence Intervals; Population Variance Unknown; T-score; Exercise.html	81 bytes
08. Margin of Error.mp4	23.1 MB
08. Margin of Error.vtt	6.4 KB
09. Confidence intervals. Two means. Dependent samples.mp4	45.0 MB
09. Confidence intervals. Two means. Dependent samples.vtt	8.5 KB
10. Confidence intervals. Two means. Dependent samples Exercise.html	81 bytes
11. Confidence intervals. Two means. Independent Samples (Part 1).mp4	12.0 MB
11. Confidence intervals. Two means. Independent Samples (Part 1).vtt	6.3 KB
12. Confidence intervals. Two means. Independent Samples (Part 1). Exercise.html	81 bytes
13. Confidence intervals. Two means. Independent Samples (Part 2).mp4	14.6 MB
13. Confidence intervals. Two means. Independent Samples (Part 2).vtt	4.7 KB
14. Confidence intervals. Two means. Independent Samples (Part 2). Exercise.html	81 bytes
15. Confidence intervals. Two means. Independent Samples (Part 3).mp4	6.9 MB
15. Confidence intervals. Two means. Independent Samples (Part 3).vtt	2.0 KB
02. 3.9.Population-variance-known-z-score-lesson.xlsx	11.2 KB
02. 3.9.The-z-table.xlsx	25.6 KB
03. 3.9.Population-variance-known-z-score-exercise-solution.xlsx	11.2 KB
03. 3.9.Population-variance-known-z-score-exercise.xlsx	10.8 KB
03. 3.9.The-z-table.xlsx	25.6 KB
06. 3.11.Population-variance-unknown-t-score-lesson.xlsx	10.8 KB
06. 3.11.The-t-table.xlsx	15.8 KB
07. 3.11.Population-variance-unknown-t-score-exercise-solution.xlsx	11.1 KB
07. 3.11.Population-variance-unknown-t-score-exercise.xlsx	10.6 KB
07. 3.11.The-t-table.xlsx	15.8 KB
09. 3.13.Confidence-intervals.Two-means.Dependent-samples-lesson.xlsx	10.5 KB
10. 3.13.Confidence-intervals.Two-means.Dependent-samples-exercise-solution.xlsx	14.2 KB
10. 3.13.Confidence-intervals.Two-means.Dependent-samples-exercise.xlsx	13.7 KB
11. 3.14.Confidence-intervals.Two-means.Independent-samples-Part-1-lesson.xlsx	9.8 KB
12. 3.14.Confidence-intervals.Two-means.Independent-samples-Part-1-exercise-solution.xlsx	10.1 KB
12. 3.14.Confidence-intervals.Two-means.Independent-samples-Part-1-exercise.xlsx	9.8 KB
13. 3.15.Confidence-intervals.Two-means.Independent-samples-Part-2-lesson.xlsx	9.5 KB
14. 3.15.Confidence-intervals.Two-means.Independent-samples-Part-2-exercise-solution.xlsx	9.8 KB
14. 3.15.Confidence-intervals.Two-means.Independent-samples-Part-2-exercise.xlsx	9.2 KB
01. Practical Example Inferential Statistics.mp4	69.0 MB
01. Practical Example Inferential Statistics.vtt	13.9 KB
02. Practical Example Inferential Statistics Exercise.html	81 bytes
01. 3.17.Practical-example.Confidence-intervals-lesson.xlsx	1.7 MB
02. 3.17.Practical-example.Confidence-intervals-exercise-solution.xlsx	1.8 MB
02. 3.17.Practical-example.Confidence-intervals-exercise.xlsx	1.7 MB
01. Null vs Alternative Hypothesis.mp4	31.9 MB
01. Null vs Alternative Hypothesis.vtt	7.2 KB
02. Further Reading on Null and Alternative Hypothesis.html	2.3 KB
03. Rejection Region and Significance Level.mp4	38.7 MB
03. Rejection Region and Significance Level.vtt	8.6 KB
04. Type I Error and Type II Error.mp4	15.3 MB
04. Type I Error and Type II Error.vtt	5.5 KB
05. Test for the Mean. Population Variance Known.mp4	36.9 MB
05. Test for the Mean. Population Variance Known.vtt	8.1 KB
06. Test for the Mean. Population Variance Known Exercise.html	81 bytes
07. p-value.mp4	33.7 MB
07. p-value.vtt	5.3 KB
08. Test for the Mean. Population Variance Unknown.mp4	19.7 MB
08. Test for the Mean. Population Variance Unknown.vtt	6.0 KB
09. Test for the Mean. Population Variance Unknown Exercise.html	81 bytes
10. Test for the Mean. Dependent Samples.mp4	32.8 MB
10. Test for the Mean. Dependent Samples.vtt	6.8 KB
11. Test for the Mean. Dependent Samples Exercise.html	81 bytes
12. Test for the mean. Independent Samples (Part 1).mp4	15.4 MB
12. Test for the mean. Independent Samples (Part 1).vtt	5.5 KB
13. Test for the mean. Independent Samples (Part 1). Exercise.html	81 bytes
14. Test for the mean. Independent Samples (Part 2).mp4	24.4 MB
14. Test for the mean. Independent Samples (Part 2).vtt	5.4 KB
15. Test for the mean. Independent Samples (Part 2). Exercise.html	81 bytes
01. Course-notes-hypothesis-testing.pdf	656.4 KB
03. Course-notes-hypothesis-testing.pdf	656.4 KB
05. 4.4.Test-for-the-mean.Population-variance-known-lesson.xlsx	11.0 KB
06. 4.4.Test-for-the-mean.Population-variance-known-exercise-solution.xlsx	11.2 KB
06. 4.4.Test-for-the-mean.Population-variance-known-exercise.xlsx	11.0 KB
07. Online-p-value-calculator.pdf	1.2 MB
08. 4.6.Test-for-the-mean.Population-variance-unknown-lesson.xlsx	14.5 KB
09. 4.6.Test-for-the-mean.Population-variance-unknown-exercise-solution.xlsx	12.6 KB
09. 4.6.Test-for-the-mean.Population-variance-unknown-exercise.xlsx	11.3 KB
10. 4.7.Test-for-the-mean.Dependent-samples-lesson.xlsx	9.8 KB
11. 4.7.Test-for-the-mean.Dependent-samples-exercise-solution.xlsx	14.4 KB
11. 4.7.Test-for-the-mean.Dependent-samples-exercise.xlsx	12.8 KB
12. 4.8.Test-for-the-mean.Independent-samples-Part-1-lesson.xlsx	9.6 KB
13. 4.8.Test-for-the-mean.Independent-samples-Part-1-exercise-solution.xlsx	11.2 KB
13. 4.8.Test-for-the-mean.Independent-samples-Part-1-exercise.xlsx	10.8 KB
14. 4.9.Test-for-the-mean.Independent-samples-Part-2-lesson.xlsx	9.3 KB
15. 4.9.Test-for-the-mean.Independent-samples-Part-2-exercise-2-solution.xlsx	11.4 KB
15. 4.9.Test-for-the-mean.Independent-samples-Part-2-exercise-2.xlsx	10.5 KB
01. Practical Example Hypothesis Testing.mp4	45.8 MB
01. Practical Example Hypothesis Testing.vtt	8.6 KB
02. Practical Example Hypothesis Testing Exercise.html	81 bytes
01. 4.10.Hypothesis-testing-section-practical-example.xlsx	51.9 KB
02. 4.10.Hypothesis-testing-section-practical-example-exercise-solution.xlsx	44.3 KB
02. 4.10.Hypothesis-testing-section-practical-example-exercise.xlsx	43.7 KB
01. Introduction to Programming.mp4	14.9 MB
01. Introduction to Programming.vtt	7.3 KB
02. Why Python.mp4	12.2 MB
02. Why Python.vtt	7.2 KB
03. Why Jupyter.mp4	8.0 MB
03. Why Jupyter.vtt	4.2 KB
04. Installing Python and Jupyter.mp4	18.8 MB
04. Installing Python and Jupyter.vtt	4.9 KB
05. Understanding Jupyter's Interface - the Notebook Dashboard.mp4	6.1 MB
05. Understanding Jupyter's Interface - the Notebook Dashboard.vtt	3.7 KB
06. Prerequisites for Coding in the Jupyter Notebooks.mp4	19.0 MB
06. Prerequisites for Coding in the Jupyter Notebooks.vtt	7.9 KB
01. Introduction-to-Python-Course-Notes.pdf	2.2 MB
01. Variables.mp4	8.9 MB
01. Variables.vtt	4.8 KB
02. Numbers and Boolean Values in Python.mp4	6.6 MB
02. Numbers and Boolean Values in Python.vtt	3.7 KB
03. Python Strings.mp4	19.7 MB
03. Python Strings.vtt	7.7 KB
01. Introduction-to-Python-Course-Notes.pdf	2.2 MB
01. Variables-Exercise-Py3.ipynb	2.2 KB
01. Variables-Lecture-Py3.ipynb	3.6 KB
01. Variables-Solution-Py3.ipynb	3.8 KB
02. Numbers-and-Boolean-Values-Exercise-Py3.ipynb	2.3 KB
02. Numbers-and-Boolean-Values-Lecture-Py3.ipynb	3.4 KB
02. Numbers-and-Boolean-Values-Solution-Py3.ipynb	3.2 KB
03. Strings-Exercise-Py3.ipynb	2.6 KB
03. Strings-Lecture-Py3.ipynb	7.6 KB
03. Strings-Solution-Py3.ipynb	5.5 KB
01. Using Arithmetic Operators in Python.mp4	8.6 MB
01. Using Arithmetic Operators in Python.vtt	4.4 KB
02. The Double Equality Sign.mp4	2.7 MB
02. The Double Equality Sign.vtt	1.9 KB
03. How to Reassign Values.mp4	1.9 MB
03. How to Reassign Values.vtt	1.3 KB
04. Add Comments.mp4	2.4 MB
04. Add Comments.vtt	1.9 KB
05. Understanding Line Continuation.mp4	1.2 MB
05. Understanding Line Continuation.vtt	1.2 KB
06. Indexing Elements.mp4	2.4 MB
06. Indexing Elements.vtt	1.7 KB
07. Structuring with Indentation.mp4	2.8 MB
07. Structuring with Indentation.vtt	2.3 KB
01. Arithmetic-Operators-Exercise-Py3.ipynb	2.6 KB
01. Arithmetic-Operators-Lecture-Py3.ipynb	3.5 KB
01. Arithmetic-Operators-Solution-Py3.ipynb	4.2 KB
02. The-Double-Equality-Sign-Exercise-Py3.ipynb	838 bytes
02. The-Double-Equality-Sign-Lecture-Py3.ipynb	1.4 KB
02. The-Double-Equality-Sign-Solution-Py3.ipynb	1.1 KB
03. Reassign-Values-Exercise-Py3.ipynb	1.7 KB
03. Reassign-Values-Lecture-Py3.ipynb	3.1 KB
03. Reassign-Values-Solution-Py3.ipynb	2.1 KB
04. Add-Comments-Lecture-Py3.ipynb	1.0 KB
05. Line-Continuation-Exercise-Py3.ipynb	1.1 KB
05. Line-Continuation-Lecture-Py3.ipynb	779 bytes
05. Line-Continuation-Solution-Py3.ipynb	1.5 KB
06. Indexing-Elements-Exercise-Py3.ipynb	1.3 KB
06. Indexing-Elements-Lecture-Py3.ipynb	1.3 KB
06. Indexing-Elements-Solution-Py3.ipynb	2.2 KB
07. Structure-Your-Code-with-Indentation-Exercise-Py3.ipynb	956 bytes
07. Structure-Your-Code-with-Indentation-Lecture-Py3.ipynb	958 bytes
07. Structure-Your-Code-with-Indentation-Solution-Py3.ipynb	1.5 KB
01. Comparison Operators.mp4	4.2 MB
01. Comparison Operators.vtt	2.6 KB
02. Logical and Identity Operators.mp4	19.0 MB
02. Logical and Identity Operators.vtt	6.0 KB
01. Comparison-Operators-Exercise-Py3.ipynb	1.6 KB
01. Comparison-Operators-Lecture-Py3.ipynb	2.5 KB
01. Comparison-Operators-Solution-Py3.ipynb	2.4 KB
02. Logical-and-Identity-Operators-Lecture-Py3.ipynb	5.9 KB
02. Logical-and-Identity-Operators-Solution-Py3.ipynb	3.4 KB
01. The IF Statement.mp4	6.7 MB
01. The IF Statement.vtt	3.7 KB
02. The ELSE Statement.mp4	6.0 MB
02. The ELSE Statement.vtt	3.2 KB
03. The ELIF Statement.mp4	14.2 MB
03. The ELIF Statement.vtt	6.8 KB
04. A Note on Boolean Values.mp4	4.2 MB
04. A Note on Boolean Values.vtt	3.1 KB
01. Introduction-to-the-If-Statement-Exercise-Py3.ipynb	1.5 KB
01. Introduction-to-the-If-Statement-Lecture-Py3.ipynb	1.1 KB
01. Introduction-to-the-If-Statement-Solution-Py3.ipynb	2.2 KB
02. Add-an-Else-Statement-Exercise-Py3.ipynb	1.0 KB
02. Add-an-Else-Statement-Lecture-Py3.ipynb	1.8 KB
02. Add-an-Else-Statement-Solution-Py3.ipynb	1.4 KB
03. Else-If-for-Brief-Elif-Exercise-Py3.ipynb	1.7 KB
03. Else-If-for-Brief-Elif-Lecture-Py3.ipynb	3.2 KB
03. Else-If-for-Brief-Elif-Solution-Py3.ipynb	2.4 KB
04. A-Note-on-Boolean-Values-Lecture-Py3.ipynb	791 bytes
01. Defining a Function in Python.mp4	3.2 MB
01. Defining a Function in Python.vtt	2.6 KB
02. How to Create a Function with a Parameter.mp4	10.0 MB
02. How to Create a Function with a Parameter.vtt	4.5 KB
03. Defining a Function in Python - Part II.mp4	6.5 MB
03. Defining a Function in Python - Part II.vtt	3.1 KB
04. How to Use a Function within a Function.mp4	3.2 MB
04. How to Use a Function within a Function.vtt	2.1 KB
05. Conditional Statements and Functions.mp4	6.0 MB
05. Conditional Statements and Functions.vtt	3.6 KB
06. Functions Containing a Few Arguments.mp4	2.8 MB
06. Functions Containing a Few Arguments.vtt	1.4 KB
07. Built-in Functions in Python.mp4	10.2 MB
07. Built-in Functions in Python.vtt	4.3 KB
01. Defining-a-Function-in-Python-Lecture-Py3.ipynb	868 bytes
02. Creating-a-Function-with-a-Parameter-Exercise-Py3.ipynb	1.2 KB
02. Creating-a-Function-with-a-Parameter-Lecture-Py3.ipynb	1.6 KB
02. Creating-a-Function-with-a-Parameter-Solution-Py3.ipynb	1.8 KB
03. Another-Way-to-Define-a-Function-Exercise-Py3.ipynb	1.2 KB
03. Another-Way-to-Define-a-Function-Lecture-Py3.ipynb	3.3 KB
03. Another-Way-to-Define-a-Function-Solution-Py3.ipynb	2.0 KB
04. 0.6.4-Using-a-Function-in-another-Function-Exercise-Py3.ipynb	1.0 KB
04. 0.6.4-Using-a-Function-in-another-Function-Lecture-Py3.ipynb	1015 bytes
04. 0.6.4-Using-a-Function-in-another-Function-Solution-Py3.ipynb	1.6 KB
05. Combining-Conditional-Statements-and-Functions-Exercise-Py3.ipynb	1.1 KB
05. Combining-Conditional-Statements-and-Functions-Lecture-Py3.ipynb	1.3 KB
05. Combining-Conditional-Statements-and-Functions-Solution-Py3.ipynb	1.6 KB
06. Creating-Functions-Containing-a-Few-Arguments-Lecture-Py3.ipynb	1.7 KB
07. Notable-Built-In-Functions-in-Python-Exercise-Py3.ipynb	3.7 KB
07. Notable-Built-In-Functions-in-Python-Lecture-Py3.ipynb	4.5 KB
07. Notable-Built-In-Functions-in-Python-Solution-Py3.ipynb	5.5 KB
01. Lists.mp4	23.0 MB
01. Lists.vtt	10.3 KB
02. Using Methods.mp4	30.4 MB
02. Using Methods.vtt	8.7 KB
03. List Slicing.mp4	19.2 MB
03. List Slicing.vtt	5.5 KB
04. Tuples.mp4	18.2 MB
04. Tuples.vtt	7.5 KB
05. Dictionaries.mp4	32.4 MB
05. Dictionaries.vtt	8.9 KB
01. Lists-Exercise-Py3.ipynb	2.1 KB
01. Lists-Lecture-Py3.ipynb	2.7 KB
01. Lists-Solution-Py3.ipynb	3.2 KB
02. Help-Yourself-with-Methods-Exercise-Py3.ipynb	1.9 KB
02. Help-Yourself-with-Methods-Lecture-Py3.ipynb	4.4 KB
02. Help-Yourself-with-Methods-Solution-Py3.ipynb	2.8 KB
03. List-Slicing-Exercise-Py3.ipynb	2.8 KB
03. List-Slicing-Lecture-Py3.ipynb	5.0 KB
03. List-Slicing-Solution-Py3.ipynb	4.3 KB
04. Tuples-Exercise-Py3.ipynb	2.1 KB
04. Tuples-Lecture-Py3.ipynb	2.9 KB
04. Tuples-Solution-Py3.ipynb	4.6 KB
05. Dictionaries-Exercise-Py3.ipynb	2.9 KB
05. Dictionaries-Lecture-Py3.ipynb	4.4 KB
05. Dictionaries-Solution-Py3.ipynb	6.2 KB
01. For Loops.mp4	13.0 MB
01. For Loops.vtt	6.8 KB
02. While Loops and Incrementing.mp4	20.2 MB
02. While Loops and Incrementing.vtt	6.0 KB
03. Lists with the range() Function.mp4	16.1 MB
03. Lists with the range() Function.vtt	8.6 KB
04. Conditional Statements and Loops.mp4	17.3 MB
04. Conditional Statements and Loops.vtt	8.0 KB
05. Conditional Statements, Functions, and Loops.mp4	4.3 MB
05. Conditional Statements, Functions, and Loops.vtt	2.5 KB
06. How to Iterate over Dictionaries.mp4	18.4 MB
06. How to Iterate over Dictionaries.vtt	7.8 KB
01. For-Loops-Exercise-Py3.ipynb	1.3 KB
01. For-Loops-Lecture-Py3.ipynb	1.3 KB
01. For-Loops-Solution-Py3.ipynb	1.8 KB
02. While-Loops-and-Incrementing-Exercise-Py3.ipynb	1.1 KB
02. While-Loops-and-Incrementing-Lecture-Py3.ipynb	1.1 KB
02. While-Loops-and-Incrementing-Solution-Py3.ipynb	1.7 KB
03. Create-Lists-with-the-range-Function-Exercise-Py3.ipynb	1.5 KB
03. Create-Lists-with-the-range-Function-Lecture-Py3.ipynb	1.3 KB
03. Create-Lists-with-the-range-Function-Solution-Py3.ipynb	2.3 KB
04. Use-Conditional-Statements-and-Loops-Together-Exercise-Py3.ipynb	2.1 KB
04. Use-Conditional-Statements-and-Loops-Together-Lecture-Py3.ipynb	1.9 KB
04. Use-Conditional-Statements-and-Loops-Together-Solution-Py3.ipynb	3.0 KB
05. All-In-Exercise-Py3.ipynb	1.3 KB
05. All-In-Lecture-Py3.ipynb	1.6 KB
05. All-In-Solution-Py3.ipynb	1.9 KB
06. Iterating-over-Dictionaries-Exercise-Py3.ipynb	2.2 KB
06. Iterating-over-Dictionaries-Lecture-Py3.ipynb	1.1 KB
06. Iterating-over-Dictionaries-Solution-Py3.ipynb	2.9 KB
01. Object Oriented Programming.mp4	8.7 MB
01. Object Oriented Programming.vtt	6.9 KB
02. Modules and Packages.mp4	2.1 MB
02. Modules and Packages.vtt	1.5 KB
03. What is the Standard Library.mp4	5.1 MB
03. What is the Standard Library.vtt	3.9 KB
04. Importing Modules in Python.mp4	9.9 MB
04. Importing Modules in Python.vtt	4.9 KB
01. Introduction to Regression Analysis.mp4	3.6 MB
01. Introduction to Regression Analysis.vtt	2.3 KB
01. Course-notes-regression-analysis.pdf	312.2 KB
01. The Linear Regression Model.mp4	13.5 MB
01. The Linear Regression Model.vtt	8.1 KB
02. Correlation vs Regression.mp4	3.8 MB
02. Correlation vs Regression.vtt	2.2 KB
03. Geometrical Representation of the Linear Regression Model.mp4	2.3 MB
03. Geometrical Representation of the Linear Regression Model.vtt	1.7 KB
04. Python Packages Installation.mp4	23.7 MB
04. Python Packages Installation.vtt	5.6 KB
05. First Regression in Python.mp4	29.6 MB
05. First Regression in Python.vtt	8.2 KB
06. First Regression in Python Exercise.html	1.3 KB
07. Using Seaborn for Graphs.mp4	7.4 MB
07. Using Seaborn for Graphs.vtt	1.6 KB
08. How to Interpret the Regression Table.mp4	28.7 MB
08. How to Interpret the Regression Table.vtt	6.3 KB
09. Decomposition of Variability.mp4	8.8 MB
09. Decomposition of Variability.vtt	4.5 KB
10. What is the OLS.mp4	22.5 MB
10. What is the OLS.vtt	3.8 KB
11. R-Squared.mp4	11.2 MB
11. R-Squared.vtt	6.8 KB
01. Course-notes-regression-analysis.pdf	312.2 KB
05. 1.01.Simple-linear-regression.csv	922 bytes
05. Simple-linear-regression-with-comments.ipynb	4.1 KB
05. Simple-linear-regression.ipynb	3.8 KB
06. real-estate-price-size.csv	1.9 KB
06. Simple-Linear-Regression-Exercise-Solution.ipynb	3.6 KB
06. Simple-Linear-Regression-Exercise.ipynb	2.8 KB
01. Multiple Linear Regression.mp4	5.7 MB
01. Multiple Linear Regression.vtt	3.5 KB
02. Adjusted R-Squared.mp4	34.2 MB
02. Adjusted R-Squared.vtt	7.5 KB
03. Multiple Linear Regression Exercise.html	76 bytes
04. Test for Significance of the Model (F-Test).mp4	7.2 MB
04. Test for Significance of the Model (F-Test).vtt	2.5 KB
05. OLS Assumptions.mp4	5.3 MB
05. OLS Assumptions.vtt	3.1 KB
06. A1 Linearity.mp4	3.6 MB
06. A1 Linearity.vtt	2.5 KB
07. A2 No Endogeneity.mp4	9.2 MB
07. A2 No Endogeneity.vtt	5.6 KB
08. A3 Normality and Homoscedasticity.mp4	27.4 MB
08. A3 Normality and Homoscedasticity.vtt	7.0 KB
09. A4 No Autocorrelation.mp4	7.9 MB
09. A4 No Autocorrelation.vtt	5.0 KB
10. A5 No Multicollinearity.mp4	7.6 MB
10. A5 No Multicollinearity.vtt	4.6 KB
11. Dealing with Categorical Data - Dummy Variables.mp4	22.6 MB
11. Dealing with Categorical Data - Dummy Variables.vtt	9.5 KB
12. Dealing with Categorical Data - Dummy Variables.html	76 bytes
13. Making Predictions with the Linear Regression.mp4	16.3 MB
13. Making Predictions with the Linear Regression.vtt	4.4 KB
02. 1.02.Multiple-linear-regression.csv	1.1 KB
02. Multiple-linear-regression-and-Adjusted-R-squared-with-comments.ipynb	2.8 KB
02. Multiple-linear-regression-and-Adjusted-R-squared.ipynb	2.1 KB
03. Multiple-Linear-Regression-Exercise-Solution.ipynb	13.4 KB
03. Multiple-Linear-Regression-Exercise.ipynb	2.5 KB
03. real-estate-price-size-year.csv	2.4 KB
11. 1.03.Dummies.csv	1.2 KB
11. Dummy-variables-with-comments.ipynb	7.1 KB
11. Dummy-Variables.ipynb	4.6 KB
12. Multiple-Linear-Regression-with-Dummies-Exercise-Solution.ipynb	18.0 KB
12. Multiple-Linear-Regression-with-Dummies-Exercise.ipynb	3.0 KB
12. real-estate-price-size-year-view.csv	3.4 KB
13. Making-predictions-with-comments.ipynb	9.4 KB
13. Making-predictions.ipynb	5.8 KB
01. What is sklearn and How is it Different from Other Packages.mp4	8.5 MB
01. What is sklearn and How is it Different from Other Packages.vtt	3.6 KB
02. How are we Going to Approach this Section.mp4	5.3 MB
02. How are we Going to Approach this Section.vtt	3.0 KB
03. Simple Linear Regression with sklearn.mp4	27.4 MB
03. Simple Linear Regression with sklearn.vtt	7.6 KB
04. Simple Linear Regression with sklearn - A StatsModels-like Summary Table.mp4	22.3 MB
04. Simple Linear Regression with sklearn - A StatsModels-like Summary Table.vtt	6.8 KB
05. A Note on Normalization.html	733 bytes
06. Simple Linear Regression with sklearn - Exercise.html	76 bytes
07. Multiple Linear Regression with sklearn.mp4	8.3 MB
07. Multiple Linear Regression with sklearn.vtt	4.3 KB
08. Calculating the Adjusted R-Squared in sklearn.mp4	16.9 MB
08. Calculating the Adjusted R-Squared in sklearn.vtt	6.7 KB
09. Calculating the Adjusted R-Squared in sklearn - Exercise.html	76 bytes
10. Feature Selection (F-regression).mp4	20.5 MB
10. Feature Selection (F-regression).vtt	6.9 KB
11. A Note on Calculation of P-values with sklearn.html	372 bytes
12. Creating a Summary Table with P-values.mp4	6.4 MB
12. Creating a Summary Table with P-values.vtt	3.0 KB
13. Multiple Linear Regression - Exercise.html	76 bytes
14. Feature Scaling (Standardization).mp4	20.4 MB
14. Feature Scaling (Standardization).vtt	8.8 KB
15. Feature Selection through Standardization of Weights.mp4	24.5 MB
15. Feature Selection through Standardization of Weights.vtt	7.6 KB
16. Predicting with the Standardized Coefficients.mp4	20.4 MB
16. Predicting with the Standardized Coefficients.vtt	5.6 KB
17. Feature Scaling (Standardization) - Exercise.html	76 bytes
18. Underfitting and Overfitting.mp4	5.8 MB
18. Underfitting and Overfitting.vtt	3.7 KB
19. Train - Test Split Explained.mp4	35.6 MB
19. Train - Test Split Explained.vtt	9.7 KB
03. 1.01.Simple-linear-regression.csv	922 bytes
03. sklearn-Simple-Linear-Regression-with-comments.ipynb	6.1 KB
03. sklearn-Simple-Linear-Regression.ipynb	4.9 KB
04. 1.01.Simple-linear-regression.csv	922 bytes
04. sklearn-Simple-Linear-Regression-with-comments.ipynb	28.4 KB
04. sklearn-Simple-Linear-Regression.ipynb	26.1 KB
06. real-estate-price-size.csv	1.9 KB
06. Simple-Linear-Regression-with-sklearn-Exercise-Solution.ipynb	26.6 KB
06. Simple-Linear-Regression-with-sklearn-Exercise.ipynb	4.1 KB
07. 1.02.Multiple-linear-regression.csv	1.1 KB
07. sklearn-Multiple-Linear-Regression-with-comments.ipynb	8.7 KB
07. sklearn-Multiple-Linear-Regression.ipynb	7.8 KB
08. 1.02.Multiple-linear-regression.csv	1.1 KB
08. sklearn-Multiple-Linear-Regression-and-Adjusted-R-squared-with-comments.ipynb	10.4 KB
08. sklearn-Multiple-Linear-Regression-and-Adjusted-R-squared.ipynb	9.1 KB
09. 1.02.Multiple-linear-regression.csv	1.1 KB
09. sklearn-Multiple-Linear-Regression-and-Adjusted-R-squared-Exercise-Solution.ipynb	10.3 KB
09. sklearn-Multiple-Linear-Regression-and-Adjusted-R-squared-Exercise.ipynb	9.8 KB
10. 1.02.Multiple-linear-regression.csv	1.1 KB
10. sklearn-Feature-Selection-with-F-regression-with-comments.ipynb	13.0 KB
10. sklearn-Feature-Selection-with-F-regression.ipynb	10.4 KB
11. 1.02.Multiple-linear-regression.csv	1.1 KB
11. sklearn-How-to-properly-include-p-values.ipynb	12.7 KB
12. 1.02.Multiple-linear-regression.csv	1.1 KB
12. sklearn-Multiple-Linear-Regression-Summary-Table-with-comments.ipynb	16.6 KB
12. sklearn-Multiple-Linear-Regression-Summary-Table.ipynb	13.7 KB
13. real-estate-price-size-year.csv	2.4 KB
13. sklearn-Multiple-Linear-Regression-Exercise-Solution.ipynb	15.4 KB
13. sklearn-Multiple-Linear-Regression-Exercise.ipynb	5.7 KB
14. 1.02.Multiple-linear-regression.csv	1.1 KB
14. SKLEAR-1.IPY	12.9 KB
14. sklearn-Feature-Selection-through-Feature-Scaling-Standardization-Part-1.ipynb	11.7 KB
15. 1.02.Multiple-linear-regression.csv	1.1 KB
15. SKLEAR-1.IPY	16.8 KB
15. sklearn-Feature-Selection-through-Feature-Scaling-Standardization-Part-2.ipynb	14.9 KB
16. 1.02.Multiple-linear-regression.csv	1.1 KB
16. sklearn-Making-Predictions-with-the-Standardized-Coefficients-with-comments.ipynb	22.0 KB
16. sklearn-Making-Predictions-with-the-Standardized-Coefficients.ipynb	29.8 KB
17. real-estate-price-size-year.csv	2.4 KB
17. sklearn-Feature-Scaling-Exercise-Solution.ipynb	16.3 KB
17. sklearn-Feature-Scaling-Exercise.ipynb	6.1 KB
19. sklearn-Train-Test-Split-with-comments.ipynb	9.0 KB
19. sklearn-Train-Test-Split.ipynb	7.2 KB
01. Practical Example Linear Regression (Part 1).mp4	84.7 MB
01. Practical Example Linear Regression (Part 1).vtt	14.9 KB
02. Practical Example Linear Regression (Part 2).mp4	31.9 MB
02. Practical Example Linear Regression (Part 2).vtt	8.3 KB
03. A Note on Multicollinearity.html	849 bytes
04. Practical Example Linear Regression (Part 3).mp4	16.7 MB
04. Practical Example Linear Regression (Part 3).vtt	4.5 KB
05. Dummies and Variance Inflation Factor - Exercise.html	76 bytes
06. Practical Example Linear Regression (Part 4).mp4	39.4 MB
06. Practical Example Linear Regression (Part 4).vtt	11.9 KB
07. Dummy Variables - Exercise.html	713 bytes
08. Practical Example Linear Regression (Part 5).mp4	50.4 MB
08. Practical Example Linear Regression (Part 5).vtt	11.1 KB
09. Linear Regression - Exercise.html	503 bytes
01. 1.04.Real-life-example.csv	219.8 KB
01. sklearn-Linear-Regression-Practical-Example-Part-1-with-comments.ipynb	171.4 KB
01. sklearn-Linear-Regression-Practical-Example-Part-1.ipynb	166.9 KB
02. 1.04.Real-life-example.csv	219.8 KB
02. sklearn-Linear-Regression-Practical-Example-Part-2-with-comments.ipynb	335.6 KB
02. sklearn-Linear-Regression-Practical-Example-Part-2.ipynb	328.7 KB
04. sklearn-Linear-Regression-Practical-Example-Part-3-with-comments.ipynb	351.5 KB
04. sklearn-Linear-Regression-Practical-Example-Part-3.ipynb	343.6 KB
05. 1.04.Real-life-example.csv	219.8 KB
05. sklearn-Dummies-and-VIF-Exercise-Solution.ipynb	370.2 KB
05. sklearn-Dummies-and-VIF-Exercise.ipynb	344.6 KB
06. 1.04.Real-life-example.csv	219.8 KB
06. sklearn-Linear-Regression-Practical-Example-Part-4-with-comments.ipynb	407.6 KB
06. sklearn-Linear-Regression-Practical-Example-Part-4.ipynb	397.2 KB
08. 1.04.Real-life-example.csv	219.8 KB
08. sklearn-Linear-Regression-Practical-Example-Part-5-with-comments.ipynb	711.0 KB
08. sklearn-Linear-Regression-Practical-Example-Part-5.ipynb	698.4 KB
01. Introduction to Logistic Regression.mp4	5.9 MB
01. Introduction to Logistic Regression.vtt	1.8 KB
02. A Simple Example in Python.mp4	21.9 MB
02. A Simple Example in Python.vtt	5.9 KB
03. Logistic vs Logit Function.mp4	23.7 MB
03. Logistic vs Logit Function.vtt	5.1 KB
04. Building a Logistic Regression.mp4	8.6 MB
04. Building a Logistic Regression.vtt	3.5 KB
05. Building a Logistic Regression - Exercise.html	87 bytes
06. An Invaluable Coding Tip.mp4	18.8 MB
06. An Invaluable Coding Tip.vtt	3.1 KB
07. Understanding Logistic Regression Tables.mp4	14.6 MB
07. Understanding Logistic Regression Tables.vtt	5.6 KB
08. Understanding Logistic Regression Tables - Exercise.html	87 bytes
09. What do the Odds Actually Mean.mp4	11.4 MB
09. What do the Odds Actually Mean.vtt	4.4 KB
10. Binary Predictors in a Logistic Regression.mp4	24.9 MB
10. Binary Predictors in a Logistic Regression.vtt	5.3 KB
11. Binary Predictors in a Logistic Regression - Exercise.html	87 bytes
12. Calculating the Accuracy of the Model.mp4	20.3 MB
12. Calculating the Accuracy of the Model.vtt	4.3 KB
13. Calculating the Accuracy of the Model.html	87 bytes
14. Underfitting and Overfitting.mp4	7.5 MB
14. Underfitting and Overfitting.vtt	5.2 KB
15. Testing the Model.mp4	21.6 MB
15. Testing the Model.vtt	6.5 KB
16. Testing the Model - Exercise.html	87 bytes
01. Course-Notes-Logistic-Regression.pdf	335.2 KB
02. 2.01.Admittance.csv	1.6 KB
02. Admittance-with-comments.ipynb	5.3 KB
02. Admittance.ipynb	3.5 KB
02. Course-Notes-Logistic-Regression.pdf	335.2 KB
04. Admittance-regression-summary-error.ipynb	2.5 KB
04. Admittance-regression-tables-fixed-error.ipynb	4.1 KB
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05. Building-a-Logistic-Regression-Exercise.ipynb	2.9 KB
05. Building-a-Logistic-Regression-Solution.ipynb	4.4 KB
05. Example-bank-data.csv	6.2 KB
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08. Understanding-Logistic-Regression-Tables-Exercise.ipynb	3.2 KB
08. Understanding-Logistic-Regression-Tables-Solution.ipynb	4.8 KB
10. 2.02.Binary-predictors.csv	2.6 KB
10. Binary-predictors.ipynb	2.4 KB
11. Bank-data.csv	19.5 KB
11. Binary-Predictors-in-a-Logistic-Regression-Exercise.ipynb	2.5 KB
11. Binary-Predictors-in-a-Logistic-Regression-Solution.ipynb	4.5 KB
12. Accuracy-with-comments.ipynb	11.7 KB
12. Accuracy.ipynb	3.6 KB
13. Bank-data.csv	19.5 KB
13. Calculating-the-Accuracy-of-the-Model-Exercise.ipynb	5.4 KB
13. Calculating-the-Accuracy-of-the-Model-Solution.ipynb	81.2 KB
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15. Testing-the-model-with-comments.ipynb	7.6 KB
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16. Bank-data-testing.csv	8.3 KB
16. Bank-data.csv	19.5 KB
16. Testing-the-Model-Exercise.ipynb	6.8 KB
16. Testing-the-Model-Solution.ipynb	111.1 KB
01. Introduction to Cluster Analysis.mp4	14.5 MB
01. Introduction to Cluster Analysis.vtt	5.0 KB
02. Some Examples of Clusters.mp4	35.9 MB
02. Some Examples of Clusters.vtt	6.3 KB
03. Difference between Classification and Clustering.mp4	9.7 MB
03. Difference between Classification and Clustering.vtt	3.6 KB
04. Math Prerequisites.mp4	5.3 MB
04. Math Prerequisites.vtt	4.4 KB
01. Course-Notes-Cluster-Analysis.pdf	208.7 KB
02. Course-Notes-Cluster-Analysis.pdf	208.7 KB
01. K-Means Clustering.mp4	10.8 MB
01. K-Means Clustering.vtt	6.6 KB
02. A Simple Example of Clustering.mp4	34.2 MB
02. A Simple Example of Clustering.vtt	9.7 KB
03. A Simple Example of Clustering - Exercise.html	87 bytes
04. Clustering Categorical Data.mp4	10.4 MB
04. Clustering Categorical Data.vtt	3.3 KB
05. Clustering Categorical Data - Exercise.html	87 bytes
06. How to Choose the Number of Clusters.mp4	26.9 MB
06. How to Choose the Number of Clusters.vtt	7.6 KB
07. How to Choose the Number of Clusters - Exercise.html	87 bytes
08. Pros and Cons of K-Means Clustering.mp4	11.1 MB
08. Pros and Cons of K-Means Clustering.vtt	4.6 KB
09. To Standardize or not to Standardize.mp4	10.9 MB
09. To Standardize or not to Standardize.vtt	6.3 KB
10. Relationship between Clustering and Regression.mp4	3.5 MB
10. Relationship between Clustering and Regression.vtt	2.3 KB
11. Market Segmentation with Cluster Analysis (Part 1).mp4	28.0 MB
11. Market Segmentation with Cluster Analysis (Part 1).vtt	7.5 KB
12. Market Segmentation with Cluster Analysis (Part 2).mp4	34.1 MB
12. Market Segmentation with Cluster Analysis (Part 2).vtt	9.1 KB
13. How is Clustering Useful.mp4	37.4 MB
13. How is Clustering Useful.vtt	6.8 KB
14. EXERCISE Species Segmentation with Cluster Analysis (Part 1).html	87 bytes
15. EXERCISE Species Segmentation with Cluster Analysis (Part 2).html	87 bytes
02. 3.01.Country-clusters.csv	200 bytes
02. Country-clusters-with-comments.ipynb	5.8 KB
02. Country-clusters.ipynb	3.3 KB
03. A-Simple-Example-of-Clustering-Exercise.ipynb	3.6 KB
03. A-Simple-Example-of-Clustering-Solution.ipynb	4.6 KB
03. Countries-exercise.csv	8.3 KB
04. Categorical-data-with-comments.ipynb	5.6 KB
04. Categorical-data.ipynb	3.3 KB
05. Categorical.csv	10.3 KB
05. Clustering-Categorical-Data-Exercise.ipynb	3.8 KB
05. Clustering-Categorical-Data-Solution.ipynb	4.9 KB
06. Selecting-the-number-of-clusters-with-comments.ipynb	7.5 KB
06. Selecting-the-number-of-clusters.ipynb	4.5 KB
07. Countries-exercise.csv	8.3 KB
07. How-to-Choose-the-Number-of-Clusters-Exercise.ipynb	5.5 KB
07. How-to-Choose-the-Number-of-Clusters-Solution.ipynb	8.5 KB
11. 3.12.Example.csv	283 bytes
11. Market-segmentation-example-with-comments.ipynb	5.9 KB
11. Market-segmentation-example.ipynb	3.8 KB
12. Market-segmentation-example-Part2-with-comments.ipynb	6.8 KB
12. Market-segmentation-example-Part2.ipynb	4.7 KB
14. iris-dataset.csv	2.4 KB
14. Species-Segmentation-with-Cluster-Analysis-Part-1-Exercise.ipynb	4.5 KB
14. Species-Segmentation-with-Cluster-Analysis-Part-1-Solution.ipynb	7.4 KB
15. iris-dataset.csv	2.4 KB
15. iris-with-answers.csv	3.6 KB
15. Species-Segmentation-with-Cluster-Analysis-Part-2-Exercise.ipynb	10.7 KB
15. Species-Segmentation-with-Cluster-Analysis-Part-2-Solution.ipynb	15.3 KB
01. Types of Clustering.mp4	9.0 MB
01. Types of Clustering.vtt	5.1 KB
02. Dendrogram.mp4	18.3 MB
02. Dendrogram.vtt	7.6 KB
03. Heatmaps.mp4	18.5 MB
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03. Country-clusters-standardized.csv	244 bytes
03. Heatmaps-with-comments.ipynb	17.7 KB
03. Heatmaps.ipynb	1.8 KB
01. Traditional data science methods and the role of ChatGPT.mp4	26.2 MB
01. Traditional data science methods and the role of ChatGPT.vtt	7.2 KB
02. How to install ChatGPT.mp4	5.2 MB
02. How to install ChatGPT.vtt	2.0 KB
03. How ChatGPT can boost your productivity.mp4	5.4 MB
03. How ChatGPT can boost your productivity.vtt	2.4 KB
04. Data Preprocessing with ChatGPT.mp4	28.7 MB
04. Data Preprocessing with ChatGPT.vtt	6.4 KB
05. First attempt at machine learning with ChatGPT.mp4	36.7 MB
05. First attempt at machine learning with ChatGPT.vtt	6.4 KB
06. Analyzing a client database with ChatGPT in Python.mp4	21.6 MB
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07. Analyzing a client database with ChatGPT in Python – analyzing top products.mp4	15.2 MB
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08. Analyzing a client database with ChatGPT in Python – analyzing top clients, RFM.mp4	27.2 MB
08. Analyzing a client database with ChatGPT in Python – analyzing top clients, RFM.vtt	5.8 KB
09. Exploratory data analysis (EDA) with ChatGPT - histogram and scatter plot.mp4	21.6 MB
09. Exploratory data analysis (EDA) with ChatGPT - histogram and scatter plot.vtt	7.4 KB
10. Exploratory data analysis (EDA) with ChatGPT - correlation matrix, outlier detec.mp4	33.7 MB
10. Exploratory data analysis (EDA) with ChatGPT - correlation matrix, outlier detec.vtt	7.6 KB
11. Assignment 1.html	1.6 KB
12. Hypothesis testing with ChatGPT.mp4	14.4 MB
12. Hypothesis testing with ChatGPT.vtt	5.6 KB
13. Marvels comic book database Intro to Regular Expressions (RegEx).mp4	15.0 MB
13. Marvels comic book database Intro to Regular Expressions (RegEx).vtt	2.7 KB
14. Decoding comic book data Python Regular Expressions and ChatGPT.mp4	33.1 MB
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15. Assignment 2.html	1.6 KB
16. Algorithm recommendation Movie Database Analysis with ChatGPT.mp4	17.3 MB
16. Algorithm recommendation Movie Database Analysis with ChatGPT.vtt	4.4 KB
17. Algorithm recommendation recommendation engine for movies with ChatGPT.mp4	17.8 MB
17. Algorithm recommendation recommendation engine for movies with ChatGPT.vtt	6.4 KB
18. Ethical principles in data and AI utilization.mp4	14.7 MB
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19. Using ChatGPT for ethical considerations.mp4	33.5 MB
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04. Data-Preprocessing-Medical-Data.ipynb	7.5 KB
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05. diagnosis-mapping.csv	90 bytes
05. Medical-Data-ML-Attempt.ipynb	4.4 KB
05. patients-preprocessed.csv	3.3 KB
06. customers.csv	1.6 KB
06. orders.csv	37.7 KB
06. products.csv	1.8 KB
06. ratings.csv	3.4 KB
08. Furniture-store-data-analysis.ipynb	52.4 KB
10. Properties-analysis.ipynb	286.5 KB
10. properties.csv	2.7 KB
12. Students-Hypothesis-Testing.ipynb	5.6 KB
12. students.csv	2.1 KB
14. Marvel-Comics-Reg-Ex.ipynb	29.5 KB
16. ratings-small.csv	2.3 MB
17. Movies-Data-Base-Recommendation-Engine.ipynb	20.4 KB
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19. interactions.csv	73.3 KB
19. posts.csv	30.8 KB
19. users.csv	3.5 KB
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movies_metadata.csv	32.8 MB
01. Intro to the Case Study.mp4	10.4 MB
01. Intro to the Case Study.vtt	3.7 KB
02. The Naive Bayes Algorithm.mp4	42.1 MB
02. The Naive Bayes Algorithm.vtt	6.1 KB
03. Tokenization and Vectorization.mp4	15.8 MB
03. Tokenization and Vectorization.vtt	7.9 KB
04. Imbalanced Data Sets.mp4	6.6 MB
04. Imbalanced Data Sets.vtt	3.3 KB
05. Overcome Imbalanced Data in Machine Learning.mp4	14.6 MB
05. Overcome Imbalanced Data in Machine Learning.vtt	5.0 KB
06. Loading the Dataset and Preprocessing.mp4	14.8 MB
06. Loading the Dataset and Preprocessing.vtt	3.7 KB
07. Optimizing User Reviews Data Preprocessing & EDA.mp4	18.7 MB
07. Optimizing User Reviews Data Preprocessing & EDA.vtt	6.0 KB
08. Reg Ex for Analyzing Text Review Data.mp4	16.2 MB
08. Reg Ex for Analyzing Text Review Data.vtt	5.1 KB
09. Understanding Differences between Multinomial and Bernouilli Naive Bayes.mp4	13.9 MB
09. Understanding Differences between Multinomial and Bernouilli Naive Bayes.vtt	5.4 KB
10. Machine Learning with Naïve Bayes (First Attempt).mp4	28.1 MB
10. Machine Learning with Naïve Bayes (First Attempt).vtt	8.4 KB
11. Machine Learning with Naïve Bayes – converting the problem to a binary one.mp4	18.9 MB
11. Machine Learning with Naïve Bayes – converting the problem to a binary one.vtt	6.7 KB
12. Testing the Model on New Data.mp4	20.8 MB
12. Testing the Model on New Data.vtt	6.9 KB
12. 365-User-Reviews-Naive-Bayes-Sentiment-Analysis.ipynb	1.7 MB
12. user-courses-review-test-set.csv	19.6 KB
01. What is a Matrix.mp4	11.9 MB
01. What is a Matrix.vtt	4.6 KB
02. Scalars and Vectors.mp4	8.5 MB
02. Scalars and Vectors.vtt	4.0 KB
03. Linear Algebra and Geometry.mp4	13.7 MB
03. Linear Algebra and Geometry.vtt	4.1 KB
04. Arrays in Python - A Convenient Way To Represent Matrices.mp4	19.0 MB
04. Arrays in Python - A Convenient Way To Represent Matrices.vtt	6.2 KB
05. What is a Tensor.mp4	15.5 MB
05. What is a Tensor.vtt	3.8 KB
06. Addition and Subtraction of Matrices.mp4	22.1 MB
06. Addition and Subtraction of Matrices.vtt	4.2 KB
07. Errors when Adding Matrices.mp4	5.8 MB
07. Errors when Adding Matrices.vtt	2.7 KB
08. Transpose of a Matrix.mp4	14.2 MB
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09. Dot Product.mp4	12.8 MB
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10. Dot Product of Matrices.mp4	34.3 MB
10. Dot Product of Matrices.vtt	9.1 KB
11. Why is Linear Algebra Useful.mp4	88.5 MB
11. Why is Linear Algebra Useful.vtt	11.5 KB
04. Scalars-Vectors-and-Matrices.ipynb	4.5 KB
05. Tensors.ipynb	2.1 KB
06. Adding-and-subtracting-matrices.ipynb	3.2 KB
07. Errors-when-adding-scalars-vectors-and-matrices-in-Python.ipynb	3.2 KB
08. Tranpose-of-a-matrix.ipynb	2.9 KB
09. Dot-product.ipynb	2.1 KB
10. Dot-product-Part-2.ipynb	3.6 KB
01. What to Expect from this Part.mp4	11.7 MB
01. What to Expect from this Part.vtt	4.8 KB
01. Introduction to Neural Networks.mp4	10.5 MB
01. Introduction to Neural Networks.vtt	6.2 KB
02. Training the Model.mp4	7.7 MB
02. Training the Model.vtt	4.7 KB
03. Types of Machine Learning.mp4	13.1 MB
03. Types of Machine Learning.vtt	5.5 KB
04. The Linear Model (Linear Algebraic Version).mp4	8.0 MB
04. The Linear Model (Linear Algebraic Version).vtt	3.7 KB
05. The Linear Model with Multiple Inputs.mp4	7.9 MB
05. The Linear Model with Multiple Inputs.vtt	2.8 KB
06. The Linear model with Multiple Inputs and Multiple Outputs.mp4	16.6 MB
06. The Linear model with Multiple Inputs and Multiple Outputs.vtt	4.8 KB
07. Graphical Representation of Simple Neural Networks.mp4	7.8 MB
07. Graphical Representation of Simple Neural Networks.vtt	2.7 KB
08. What is the Objective Function.mp4	6.2 MB
08. What is the Objective Function.vtt	2.3 KB
09. Common Objective Functions L2-norm Loss.mp4	5.5 MB
09. Common Objective Functions L2-norm Loss.vtt	2.9 KB
10. Common Objective Functions Cross-Entropy Loss.mp4	9.8 MB
10. Common Objective Functions Cross-Entropy Loss.vtt	5.4 KB
11. Optimization Algorithm 1-Parameter Gradient Descent.mp4	23.6 MB
11. Optimization Algorithm 1-Parameter Gradient Descent.vtt	8.8 KB
12. Optimization Algorithm n-Parameter Gradient Descent.mp4	16.8 MB
12. Optimization Algorithm n-Parameter Gradient Descent.vtt	7.8 KB
01. Course-Notes-Section-2.pdf	578.1 KB
02. Course-Notes-Section-2.pdf	578.1 KB
11. GD-function-example.xlsx	42.3 KB
01. Basic NN Example (Part 1).mp4	9.3 MB
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02. Basic NN Example (Part 2).mp4	15.2 MB
02. Basic NN Example (Part 2).vtt	6.7 KB
03. Basic NN Example (Part 3).mp4	15.7 MB
03. Basic NN Example (Part 3).vtt	4.4 KB
04. Basic NN Example (Part 4).mp4	40.0 MB
04. Basic NN Example (Part 4).vtt	11.0 KB
05. Basic NN Example Exercises.html	1.7 KB
01. Minimal-example-Part-1.ipynb	1.2 KB
01. Shortcuts-for-Jupyter.pdf	619.2 KB
02. Minimal-example-Part-2.ipynb	3.7 KB
03. Minimal-example-Part-3.ipynb	6.8 KB
04. Minimal-example-Part-4-Complete.ipynb	11.4 KB
05. Minimal-example-All-Exercises.ipynb	12.9 KB
05. Minimal-example-Exercise-1-Solution.ipynb	69.0 KB
05. Minimal-example-Exercise-2-Solution.ipynb	61.4 KB
05. Minimal-example-Exercise-3.a.Solution.ipynb	67.9 KB
05. Minimal-example-Exercise-3.b.Solution.ipynb	67.7 KB
05. Minimal-example-Exercise-3.c.Solution.ipynb	70.1 KB
05. Minimal-example-Exercise-3.d.Solution.ipynb	84.1 KB
05. Minimal-example-Exercise-4-Solution.ipynb	66.5 KB
05. Minimal-example-Exercise-5-Solution.ipynb	68.9 KB
05. Minimal-example-Exercise-6-Solution.ipynb	61.8 KB
05. Minimal-example-Exercise-6.ipynb	61.8 KB
01. How to Install TensorFlow 2.0.mp4	27.3 MB
01. How to Install TensorFlow 2.0.vtt	6.6 KB
02. TensorFlow Outline and Comparison with Other Libraries.mp4	15.3 MB
02. TensorFlow Outline and Comparison with Other Libraries.vtt	5.5 KB
03. TensorFlow 1 vs TensorFlow 2.mp4	15.3 MB
03. TensorFlow 1 vs TensorFlow 2.vtt	4.0 KB
04. A Note on TensorFlow 2 Syntax.mp4	4.6 MB
04. A Note on TensorFlow 2 Syntax.vtt	1.4 KB
05. Types of File Formats Supporting TensorFlow.mp4	8.9 MB
05. Types of File Formats Supporting TensorFlow.vtt	3.5 KB
06. Outlining the Model with TensorFlow 2.mp4	27.0 MB
06. Outlining the Model with TensorFlow 2.vtt	8.4 KB
07. Interpreting the Result and Extracting the Weights and Bias.mp4	25.9 MB
07. Interpreting the Result and Extracting the Weights and Bias.vtt	6.7 KB
08. Customizing a TensorFlow 2 Model.mp4	16.8 MB
08. Customizing a TensorFlow 2 Model.vtt	4.3 KB
09. Basic NN with TensorFlow Exercises.html	1.3 KB
01. Shortcuts-for-Jupyter.pdf	619.2 KB
05. TensorFlow-Minimal-example-Part1.ipynb	1.7 KB
06. TensorFlow-Minimal-example-Part2.ipynb	9.1 KB
07. TensorFlow-Minimal-example-Part3.ipynb	76.5 KB
08. TensorFlow-Minimal-example-complete-with-comments.ipynb	82.3 KB
08. TensorFlow-Minimal-example-complete.ipynb	76.9 KB
09. TensorFlow-Minimal-example-All-exercises.ipynb	83.6 KB
09. TensorFlow-Minimal-example-Exercise-1-Solution.ipynb	28.0 KB
09. TensorFlow-Minimal-Example-Exercise-2-1-Solution.ipynb	83.7 KB
09. TensorFlow-Minimal-Example-Exercise-2-2-Solution.ipynb	77.5 KB
09. TensorFlow-Minimal-Example-Exercise-3-Solution.ipynb	84.4 KB
01. What is a Layer.mp4	5.2 MB
01. What is a Layer.vtt	2.7 KB
02. What is a Deep Net.mp4	9.1 MB
02. What is a Deep Net.vtt	3.3 KB
03. Digging into a Deep Net.mp4	23.7 MB
03. Digging into a Deep Net.vtt	6.9 KB
04. Non-Linearities and their Purpose.mp4	22.5 MB
04. Non-Linearities and their Purpose.vtt	4.2 KB
05. Activation Functions.mp4	8.8 MB
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06. Activation Functions Softmax Activation.mp4	8.7 MB
06. Activation Functions Softmax Activation.vtt	4.5 KB
07. Backpropagation.mp4	20.3 MB
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08. Backpropagation Picture.mp4	8.1 MB
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09. Backpropagation - A Peek into the Mathematics of Optimization.html	543 bytes
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02. Course-Notes-Section-6.pdf	936.4 KB
09. Backpropagation-a-peek-into-the-Mathematics-of-Optimization.pdf	182.4 KB
01. What is Overfitting.mp4	10.8 MB
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02. Underfitting and Overfitting for Classification.mp4	14.0 MB
02. Underfitting and Overfitting for Classification.vtt	2.8 KB
03. What is Validation.mp4	8.4 MB
03. What is Validation.vtt	5.0 KB
04. Training, Validation, and Test Datasets.mp4	9.4 MB
04. Training, Validation, and Test Datasets.vtt	3.4 KB
05. N-Fold Cross Validation.mp4	6.2 MB
05. N-Fold Cross Validation.vtt	4.4 KB
06. Early Stopping or When to Stop Training.mp4	10.3 MB
06. Early Stopping or When to Stop Training.vtt	7.0 KB
01. What is Initialization.mp4	8.9 MB
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02. Types of Simple Initializations.mp4	5.7 MB
02. Types of Simple Initializations.vtt	3.8 KB
03. State-of-the-Art Method - (Xavier) Glorot Initialization.mp4	5.5 MB
03. State-of-the-Art Method - (Xavier) Glorot Initialization.vtt	3.8 KB
01. Stochastic Gradient Descent.mp4	7.8 MB
01. Stochastic Gradient Descent.vtt	4.8 KB
02. Problems with Gradient Descent.mp4	3.7 MB
02. Problems with Gradient Descent.vtt	3.0 KB
03. Momentum.mp4	5.2 MB
03. Momentum.vtt	3.6 KB
04. Learning Rate Schedules, or How to Choose the Optimal Learning Rate.mp4	17.5 MB
04. Learning Rate Schedules, or How to Choose the Optimal Learning Rate.vtt	6.3 KB
05. Learning Rate Schedules Visualized.mp4	3.2 MB
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06. Adaptive Learning Rate Schedules (AdaGrad and RMSprop ).mp4	8.5 MB
06. Adaptive Learning Rate Schedules (AdaGrad and RMSprop ).vtt	5.6 KB
07. Adam (Adaptive Moment Estimation).mp4	7.1 MB
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01. Preprocessing Introduction.mp4	9.2 MB
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02. Types of Basic Preprocessing.mp4	3.2 MB
02. Types of Basic Preprocessing.vtt	1.9 KB
03. Standardization.mp4	12.1 MB
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04. Preprocessing Categorical Data.mp4	5.4 MB
04. Preprocessing Categorical Data.vtt	2.8 KB
05. Binary and One-Hot Encoding.mp4	8.5 MB
05. Binary and One-Hot Encoding.vtt	5.3 KB
01. MNIST The Dataset.mp4	4.5 MB
01. MNIST The Dataset.vtt	3.6 KB
02. MNIST How to Tackle the MNIST.mp4	7.9 MB
02. MNIST How to Tackle the MNIST.vtt	3.6 KB
03. MNIST Importing the Relevant Packages and Loading the Data.mp4	12.2 MB
03. MNIST Importing the Relevant Packages and Loading the Data.vtt	3.0 KB
04. MNIST Preprocess the Data - Create a Validation Set and Scale It.mp4	22.9 MB
04. MNIST Preprocess the Data - Create a Validation Set and Scale It.vtt	6.5 KB
05. MNIST Preprocess the Data - Scale the Test Data - Exercise.html	79 bytes
06. MNIST Preprocess the Data - Shuffle and Batch.mp4	32.7 MB
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07. MNIST Preprocess the Data - Shuffle and Batch - Exercise.html	79 bytes
08. MNIST Outline the Model.mp4	22.1 MB
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09. MNIST Select the Loss and the Optimizer.mp4	10.7 MB
09. MNIST Select the Loss and the Optimizer.vtt	3.0 KB
10. MNIST Learning.mp4	31.0 MB
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11. MNIST - Exercises.html	2.0 KB
12. MNIST Testing the Model.mp4	22.6 MB
12. MNIST Testing the Model.vtt	6.0 KB
03. TensorFlow-MNIST-Part1-with-comments.ipynb	4.0 KB
05. TensorFlow-MNIST-Part2-with-comments.ipynb	6.4 KB
07. TensorFlow-MNIST-Part3-with-comments.ipynb	8.6 KB
08. TensorFlow-MNIST-Part4-with-comments.ipynb	10.5 KB
09. TensorFlow-MNIST-Part5-with-comments.ipynb	11.0 KB
10. TensorFlow-MNIST-Part6-with-comments.ipynb	12.5 KB
11. 1.TensorFlow-MNIST-Width-Solution.ipynb	14.8 KB
11. 2.TensorFlow-MNIST-Depth-Solution.ipynb	15.3 KB
11. 3.TensorFlow-MNIST-Width-and-Depth-Solution.ipynb	15.3 KB
11. 4.TensorFlow-MNIST-Activation-functions-Part-1-Solution.ipynb	15.1 KB
11. 5.TensorFlow-MNIST-Activation-functions-Part-2-Solution.ipynb	14.7 KB
11. 6.TensorFlow-MNIST-Batch-size-Part-1-Solution.ipynb	15.1 KB
11. 7.TensorFlow-MNIST-Batch-size-Part-2-Solution.ipynb	15.2 KB
11. 8.TensorFlow-MNIST-Learning-rate-Part-1-Solution.ipynb	20.6 KB
11. 9.TensorFlow-MNIST-Learning-rate-Part-2-Solution.ipynb	15.8 KB
11. TensorFlow-MNIST-All-Exercises.ipynb	16.7 KB
11. TensorFlow-MNIST-around-98-percent-accuracy.ipynb	15.0 KB
12. TensorFlow-MNIST-complete-with-comments.ipynb	14.5 KB
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01. Business Case Exploring the Dataset and Identifying Predictors.mp4	51.3 MB
01. Business Case Exploring the Dataset and Identifying Predictors.vtt	11.0 KB
02. Business Case Outlining the Solution.mp4	3.0 MB
02. Business Case Outlining the Solution.vtt	1.9 KB
03. Business Case Balancing the Dataset.mp4	22.3 MB
03. Business Case Balancing the Dataset.vtt	4.3 KB
04. Business Case Preprocessing the Data.mp4	73.8 MB
04. Business Case Preprocessing the Data.vtt	13.6 KB
05. Business Case Preprocessing the Data - Exercise.html	370 bytes
06. Business Case Load the Preprocessed Data.mp4	13.8 MB
06. Business Case Load the Preprocessed Data.vtt	4.7 KB
07. Business Case Load the Preprocessed Data - Exercise.html	79 bytes
08. Business Case Learning and Interpreting the Result.mp4	29.4 MB
08. Business Case Learning and Interpreting the Result.vtt	6.3 KB
09. Business Case Setting an Early Stopping Mechanism.mp4	43.8 MB
09. Business Case Setting an Early Stopping Mechanism.vtt	8.1 KB
10. Setting an Early Stopping Mechanism - Exercise.html	192 bytes
11. Business Case Testing the Model.mp4	8.2 MB
11. Business Case Testing the Model.vtt	2.1 KB
12. Business Case Final Exercise.html	433 bytes
01. Audiobooks-data.csv	710.8 KB
04. TensorFlow-Audiobooks-Preprocessing-with-comments.ipynb	11.2 KB
04. TensorFlow-Audiobooks-Preprocessing.ipynb	5.6 KB
05. TensorFlow-Audiobooks-Preprocessing-Exercise-Solution.ipynb	10.0 KB
05. TensorFlow-Audiobooks-Preprocessing-Exercise.ipynb	8.6 KB
07. TensorFlow-Audiobooks-Machine-Learning-Part1-with-comments.ipynb	4.6 KB
08. TensorFlow-Audiobooks-Machine-Learning-Part2-with-comments.ipynb	19.7 KB
09. TensorFlow-Audiobooks-Machine-Learning-Part3-with-comments.ipynb	10.1 KB
11. TensorFlow-Audiobooks-Machine-Learning-with-comments.ipynb	12.0 KB
12. TensorFlow-Audiobooks-Machine-Learning-with-comments.ipynb	12.0 KB
01. Summary on What You've Learned.mp4	9.8 MB
01. Summary on What You've Learned.vtt	5.5 KB
02. What's Further out there in terms of Machine Learning.mp4	4.8 MB
02. What's Further out there in terms of Machine Learning.vtt	2.7 KB
03. DeepMind and Deep Learning.html	1.1 KB
04. An overview of CNNs.mp4	13.4 MB
04. An overview of CNNs.vtt	6.4 KB
05. An Overview of RNNs.mp4	7.0 MB
05. An Overview of RNNs.vtt	4.0 KB
06. An Overview of non-NN Approaches.mp4	16.1 MB
06. An Overview of non-NN Approaches.vtt	5.7 KB
01. READ ME!!!!.html	564 bytes
02. How to Install TensorFlow 1.mp4	5.0 MB
02. How to Install TensorFlow 1.vtt	3.4 KB
03. A Note on Installing Packages in Anaconda.html	2.3 KB
04. TensorFlow Intro.mp4	16.9 MB
04. TensorFlow Intro.vtt	5.3 KB
05. Actual Introduction to TensorFlow.mp4	9.0 MB
05. Actual Introduction to TensorFlow.vtt	2.3 KB
06. Types of File Formats, supporting Tensors.mp4	8.9 MB
06. Types of File Formats, supporting Tensors.vtt	3.4 KB
07. Basic NN Example with TF Inputs, Outputs, Targets, Weights, Biases.mp4	17.7 MB
07. Basic NN Example with TF Inputs, Outputs, Targets, Weights, Biases.vtt	8.0 KB
08. Basic NN Example with TF Loss Function and Gradient Descent.mp4	13.6 MB
08. Basic NN Example with TF Loss Function and Gradient Descent.vtt	4.9 KB
09. Basic NN Example with TF Model Output.mp4	17.1 MB
09. Basic NN Example with TF Model Output.vtt	7.9 KB
10. Basic NN Example with TF Exercises.html	1.6 KB
05. Shortcuts-for-Jupyter.pdf	619.2 KB
06. 5.3.TensorFlow-Minimal-example-Part-1.ipynb	3.4 KB
07. 5.4.TensorFlow-Minimal-example-Part-2.ipynb	6.2 KB
08. 5.5.TensorFlow-Minimal-example-Part-3.ipynb	8.6 KB
09. 5.6.TensorFlow-Minimal-example-complete.ipynb	12.1 KB
10. TensorFlow-Minimal-Example-All-Exercises.ipynb	14.0 KB
10. TensorFlow-Minimal-Example-Exercise-1-Solution.ipynb	23.6 KB
10. TensorFlow-Minimal-Example-Exercise-2-1-Solution.ipynb	25.5 KB
10. TensorFlow-Minimal-Example-Exercise-2-2-Solution.ipynb	25.5 KB
10. TensorFlow-Minimal-Example-Exercise-2-3-Solution.ipynb	50.0 KB
10. TensorFlow-Minimal-Example-Exercise-2-4-Solution.ipynb	21.7 KB
10. TensorFlow-Minimal-Example-Exercise-3-Solution.ipynb	26.7 KB
10. TensorFlow-Minimal-Example-Exercise-4-Solution.ipynb	27.0 KB
01. MNIST What is the MNIST Dataset.mp4	4.8 MB
01. MNIST What is the MNIST Dataset.vtt	3.6 KB
02. MNIST How to Tackle the MNIST.mp4	8.0 MB
02. MNIST How to Tackle the MNIST.vtt	3.8 KB
03. MNIST Relevant Packages.mp4	11.2 MB
03. MNIST Relevant Packages.vtt	2.2 KB
04. MNIST Model Outline.mp4	34.7 MB
04. MNIST Model Outline.vtt	9.2 KB
05. MNIST Loss and Optimization Algorithm.mp4	15.8 MB
05. MNIST Loss and Optimization Algorithm.vtt	3.6 KB
06. Calculating the Accuracy of the Model.mp4	24.4 MB
06. Calculating the Accuracy of the Model.vtt	5.3 KB
07. MNIST Batching and Early Stopping.mp4	9.5 MB
07. MNIST Batching and Early Stopping.vtt	2.8 KB
08. MNIST Learning.mp4	31.8 MB
08. MNIST Learning.vtt	10.5 KB
09. MNIST Results and Testing.mp4	38.1 MB
09. MNIST Results and Testing.vtt	8.2 KB
10. MNIST Exercises.html	2.2 KB
11. MNIST Solutions.html	2.2 KB
03. 12.3.TensorFlow-MNIST-with-comments-Part-1.ipynb	3.9 KB
04. 12.4.TensorFlow-MNIST-with-comments-Part-2.ipynb	6.1 KB
05. 12.5.TensorFlow-MNIST-with-comments-Part-3.ipynb	7.3 KB
06. 12.6.TensorFlow-MNIST-with-comments-Part-4.ipynb	7.9 KB
07. 12.7.TensorFlow-MNIST-with-comments-Part-5.ipynb	8.5 KB
08. 12.8.TensorFlow-MNIST-with-comments-Part-6.ipynb	11.5 KB
09. 12.9.TensorFlow-MNIST-with-comments.ipynb	13.0 KB
10. TensorFlow-MNIST-Exercises-All.ipynb	15.5 KB
11. 0.TensorFlow-MNIST-take-note-of-time-Solution.ipynb	14.0 KB
11. 1.TensorFlow-MNIST-Width-Solution.ipynb	14.0 KB
11. 2.TensorFlow-MNIST-Depth-Solution.ipynb	14.9 KB
11. 3.TensorFlow-MNIST-Width-and-Depth-Solution.ipynb	16.8 KB
11. 4.TensorFlow-MNIST-Activation-functions-Part-1-Solution.ipynb	14.3 KB
11. 5.TensorFlow-MNIST-Activation-functions-Part-2-Solution.ipynb	13.9 KB
11. 6.TensorFlow-MNIST-Batch-size-Part-1-Solution.ipynb	14.3 KB
11. 7.TensorFlow-MNIST-Batch-size-Part-2-Solution.ipynb	14.2 KB
11. 8.TensorFlow-MNIST-Learning-rate-Part-1-Solution.ipynb	14.1 KB
11. 9.TensorFlow-MNIST-Learning-rate-Part-2-Solution.ipynb	15.2 KB
11. TensorFlow-MNIST-around-98-percent-accuracy.ipynb	17.7 KB
01. Business Case Getting Acquainted with the Dataset.mp4	60.3 MB
01. Business Case Getting Acquainted with the Dataset.vtt	11.0 KB
02. Business Case Outlining the Solution.mp4	4.2 MB
02. Business Case Outlining the Solution.vtt	2.6 KB
03. The Importance of Working with a Balanced Dataset.mp4	27.3 MB
03. The Importance of Working with a Balanced Dataset.vtt	4.4 KB
04. Business Case Preprocessing.mp4	74.4 MB
04. Business Case Preprocessing.vtt	13.6 KB
05. Business Case Preprocessing Exercise.html	389 bytes
06. Creating a Data Provider.mp4	56.3 MB
06. Creating a Data Provider.vtt	8.3 KB
07. Business Case Model Outline.mp4	42.5 MB
07. Business Case Model Outline.vtt	7.2 KB
08. Business Case Optimization.mp4	26.9 MB
08. Business Case Optimization.vtt	6.9 KB
09. Business Case Interpretation.mp4	18.6 MB
09. Business Case Interpretation.vtt	3.1 KB
10. Business Case Testing the Model.mp4	4.4 MB
10. Business Case Testing the Model.vtt	2.7 KB
11. Business Case A Comment on the Homework.mp4	20.6 MB
11. Business Case A Comment on the Homework.vtt	5.4 KB
12. Business Case Final Exercise.html	443 bytes
01. Audiobooks-data.csv	710.8 KB
03. Audiobooks-data.csv	710.8 KB
04. Audiobooks-data.csv	710.8 KB
04. TensorFlow-Audiobooks-Preprocessing-with-comments.ipynb	11.2 KB
04. TensorFlow-Audiobooks-Preprocessing.ipynb	5.6 KB
05. Audiobooks-data.csv	710.8 KB
05. TensorFlow-Audiobooks-Preprocessing-Exercise-Solution.ipynb	10.0 KB
05. TensorFlow-Audiobooks-Preprocessing-Exercise.ipynb	8.6 KB
07. TensorFlow-Audiobooks-Outlining-the-model-with-comments.ipynb	10.3 KB
07. TensorFlow-Audiobooks-Outlining-the-model.ipynb	9.4 KB
08. TensorFlow-Audiobooks-optimizing-the-algorithm-with-comments.ipynb	12.7 KB
08. TensorFlow-Audiobooks-optimizing-the-algorithm.ipynb	10.6 KB
09. TensorFlow-Audiobooks-optimizing-the-algorithm-with-comments.ipynb	12.7 KB
09. TensorFlow-Audiobooks-optimizing-the-algorithm.ipynb	10.6 KB
11. Audiobooks-data.csv	710.8 KB
11. TensorFlow-Audiobooks-Machine-learning-Homework.ipynb	14.4 KB
11. TensorFlow-Audiobooks-Preprocessing-with-comments.ipynb	11.2 KB
12. Audiobooks-data.csv	710.8 KB
12. TensorFlow-Audiobooks-Machine-learning-Homework.ipynb	14.4 KB
12. TensorFlow-Audiobooks-Preprocessing-with-comments.ipynb	11.2 KB
01. What are Data, Servers, Clients, Requests, and Responses.mp4	19.5 MB
01. What are Data, Servers, Clients, Requests, and Responses.vtt	6.3 KB
02. What are Data Connectivity, APIs, and Endpoints.mp4	60.2 MB
02. What are Data Connectivity, APIs, and Endpoints.vtt	9.2 KB
03. Taking a Closer Look at APIs.mp4	24.5 MB
03. Taking a Closer Look at APIs.vtt	10.9 KB
04. Communication between Software Products through Text Files.mp4	17.5 MB
04. Communication between Software Products through Text Files.vtt	5.8 KB
05. Software Integration - Explained.mp4	16.0 MB
05. Software Integration - Explained.vtt	7.0 KB
01. Game Plan for this Python, SQL, and Tableau Business Exercise.mp4	19.7 MB
01. Game Plan for this Python, SQL, and Tableau Business Exercise.vtt	5.6 KB
02. The Business Task.mp4	11.3 MB
02. The Business Task.vtt	4.1 KB
03. Introducing the Data Set.mp4	24.2 MB
03. Introducing the Data Set.vtt	4.3 KB
01. What to Expect from the Following Sections.html	2.5 KB
02. Importing the Absenteeism Data in Python.mp4	19.5 MB
02. Importing the Absenteeism Data in Python.vtt	4.0 KB
03. Checking the Content of the Data Set.mp4	54.0 MB
03. Checking the Content of the Data Set.vtt	7.1 KB
04. Introduction to Terms with Multiple Meanings.mp4	18.0 MB
04. Introduction to Terms with Multiple Meanings.vtt	4.3 KB
05. What's Regression Analysis - a Quick Refresher.html	2.8 KB
06. Using a Statistical Approach towards the Solution to the Exercise.mp4	9.9 MB
06. Using a Statistical Approach towards the Solution to the Exercise.vtt	3.0 KB
07. Dropping a Column from a DataFrame in Python.mp4	41.2 MB
07. Dropping a Column from a DataFrame in Python.vtt	8.2 KB
08. EXERCISE - Dropping a Column from a DataFrame in Python.html	870 bytes
09. SOLUTION - Dropping a Column from a DataFrame in Python.html	114 bytes
10. Analyzing the Reasons for Absence.mp4	27.6 MB
10. Analyzing the Reasons for Absence.vtt	6.0 KB
11. Obtaining Dummies from a Single Feature.mp4	69.8 MB
11. Obtaining Dummies from a Single Feature.vtt	10.6 KB
12. EXERCISE - Obtaining Dummies from a Single Feature.html	129 bytes
13. SOLUTION - Obtaining Dummies from a Single Feature.html	117 bytes
14. Dropping a Dummy Variable from the Data Set.html	2.3 KB
15. More on Dummy Variables A Statistical Perspective.mp4	5.8 MB
15. More on Dummy Variables A Statistical Perspective.vtt	1.7 KB
16. Classifying the Various Reasons for Absence.mp4	51.3 MB
16. Classifying the Various Reasons for Absence.vtt	10.5 KB
17. Using .concat() in Python.mp4	27.3 MB
17. Using .concat() in Python.vtt	5.2 KB
18. EXERCISE - Using .concat() in Python.html	189 bytes
19. SOLUTION - Using .concat() in Python.html	143 bytes
20. Reordering Columns in a Pandas DataFrame in Python.mp4	10.0 MB
20. Reordering Columns in a Pandas DataFrame in Python.vtt	1.9 KB
21. EXERCISE - Reordering Columns in a Pandas DataFrame in Python.html	167 bytes
22. SOLUTION - Reordering Columns in a Pandas DataFrame in Python.html	478 bytes
23. Creating Checkpoints while Coding in Jupyter.mp4	17.3 MB
23. Creating Checkpoints while Coding in Jupyter.vtt	3.7 KB
24. EXERCISE - Creating Checkpoints while Coding in Jupyter.html	137 bytes
25. SOLUTION - Creating Checkpoints while Coding in Jupyter.html	118 bytes
26. Analyzing the Dates from the Initial Data Set.mp4	40.1 MB
26. Analyzing the Dates from the Initial Data Set.vtt	8.9 KB
27. Extracting the Month Value from the Date Column.mp4	33.9 MB
27. Extracting the Month Value from the Date Column.vtt	8.0 KB
28. Extracting the Day of the Week from the Date Column.mp4	19.1 MB
28. Extracting the Day of the Week from the Date Column.vtt	4.8 KB
29. EXERCISE - Removing the Date Column.html	1.2 KB
30. Analyzing Several Straightforward Columns for this Exercise.mp4	14.3 MB
30. Analyzing Several Straightforward Columns for this Exercise.vtt	4.6 KB
31. Working on Education, Children, and Pets.mp4	27.0 MB
31. Working on Education, Children, and Pets.vtt	6.0 KB
32. Final Remarks of this Section.mp4	13.5 MB
32. Final Remarks of this Section.vtt	2.7 KB
33. A Note on Exporting Your Data as a .csv File.html	883 bytes
01. Absenteeism-data.csv	32.0 KB
01. data-preprocessing-homework.pdf	134.5 KB
01. df-preprocessed.csv	29.1 KB
23. Absenteeism-Exercise-Preprocessing-df-reason-mod.ipynb	4.8 KB
29. Absenteeism-Exercise-Preprocessing-ChP-df-date-reason-mod.ipynb	7.3 KB
29. Absenteeism-Exercise-Preprocessing-LECTURES.ipynb	7.6 MB
29. Absenteeism-Exercise-Removing-the-Date-Column-SOLUTION.ipynb	8.3 KB
32. Absenteeism-Exercise-EXERCISES-and-SOLUTIONS.ipynb	4.1 KB
32. Absenteeism-Exercise-Preprocessing-df-preprocessed.ipynb	8.5 KB
01. Exploring the Problem with a Machine Learning Mindset.mp4	13.0 MB
01. Exploring the Problem with a Machine Learning Mindset.vtt	4.8 KB
02. Creating the Targets for the Logistic Regression.mp4	32.4 MB
02. Creating the Targets for the Logistic Regression.vtt	8.7 KB
03. Selecting the Inputs for the Logistic Regression.mp4	8.7 MB
03. Selecting the Inputs for the Logistic Regression.vtt	3.6 KB
04. Standardizing the Data.mp4	15.1 MB
04. Standardizing the Data.vtt	4.3 KB
05. Splitting the Data for Training and Testing.mp4	36.1 MB
05. Splitting the Data for Training and Testing.vtt	8.5 KB
06. Fitting the Model and Assessing its Accuracy.mp4	15.2 MB
06. Fitting the Model and Assessing its Accuracy.vtt	7.3 KB
07. Creating a Summary Table with the Coefficients and Intercept.mp4	27.0 MB
07. Creating a Summary Table with the Coefficients and Intercept.vtt	6.4 KB
08. Interpreting the Coefficients for Our Problem.mp4	41.1 MB
08. Interpreting the Coefficients for Our Problem.vtt	8.5 KB
09. Standardizing only the Numerical Variables (Creating a Custom Scaler).mp4	16.9 MB
09. Standardizing only the Numerical Variables (Creating a Custom Scaler).vtt	5.2 KB
10. Interpreting the Coefficients of the Logistic Regression.mp4	15.2 MB
10. Interpreting the Coefficients of the Logistic Regression.vtt	7.5 KB
11. Backward Elimination or How to Simplify Your Model.mp4	31.8 MB
11. Backward Elimination or How to Simplify Your Model.vtt	5.4 KB
12. Testing the Model We Created.mp4	31.6 MB
12. Testing the Model We Created.vtt	6.5 KB
13. Saving the Model and Preparing it for Deployment.mp4	25.5 MB
13. Saving the Model and Preparing it for Deployment.vtt	5.8 KB
14. ARTICLE - A Note on 'pickling'.html	2.1 KB
15. EXERCISE - Saving the Model (and Scaler).html	284 bytes
16. Preparing the Deployment of the Model through a Module.mp4	28.6 MB
16. Preparing the Deployment of the Model through a Module.vtt	5.9 KB
01. Absenteeism-preprocessed.csv	29.1 KB
01. Are You Sure You're All Set.html	519 bytes
02. Deploying the 'absenteeism_module' - Part I.mp4	19.7 MB
02. Deploying the 'absenteeism_module' - Part I.vtt	5.0 KB
03. Deploying the 'absenteeism_module' - Part II.mp4	45.1 MB
03. Deploying the 'absenteeism_module' - Part II.vtt	8.0 KB
04. Exporting the Obtained Data Set as a .csv.html	998 bytes
01. Absenteeism-Exercise-Integration.ipynb	62.4 KB
01. absenteeism-module.py	6.6 KB
01. Absenteeism-new-data.csv	1.9 KB
01. model	1.0 KB
01. scaler	1.9 KB
04. Absenteeism-Exercise-Deploying-the-absenteeism-module.ipynb	973 bytes
01. EXERCISE - Age vs Probability.html	385 bytes
02. Analyzing Age vs Probability in Tableau.mp4	38.7 MB
02. Analyzing Age vs Probability in Tableau.vtt	10.2 KB
03. EXERCISE - Reasons vs Probability.html	397 bytes
04. Analyzing Reasons vs Probability in Tableau.mp4	40.3 MB
04. Analyzing Reasons vs Probability in Tableau.vtt	9.7 KB
05. EXERCISE - Transportation Expense vs Probability.html	553 bytes
06. Analyzing Transportation Expense vs Probability in Tableau.mp4	16.5 MB
06. Analyzing Transportation Expense vs Probability in Tableau.vtt	7.6 KB
01. Absenteeism-predictions.csv	2.1 KB
02. Absenteeism-predictions.csv	2.1 KB
01. Using the .format() Method.mp4	25.7 MB
01. Using the .format() Method.vtt	12.7 KB
02. Iterating Over Range Objects.mp4	12.6 MB
02. Iterating Over Range Objects.vtt	6.4 KB
03. Introduction to Nested For Loops.mp4	12.2 MB
03. Introduction to Nested For Loops.vtt	8.5 KB
04. Triple Nested For Loops.mp4	33.0 MB
04. Triple Nested For Loops.vtt	8.5 KB
05. List Comprehensions.mp4	43.2 MB
05. List Comprehensions.vtt	12.8 KB
06. Anonymous (Lambda) Functions.mp4	22.8 MB
06. Anonymous (Lambda) Functions.vtt	10.5 KB
01. Additional-Python-Tools-Exercises.ipynb	11.4 KB
01. Additional-Python-Tools-Lectures.ipynb	13.5 KB
01. Additional-Python-Tools-Solutions.ipynb	25.5 KB
06. Additional-Python-Tools-Exercises.ipynb	11.4 KB
06. Additional-Python-Tools-Lectures.ipynb	13.5 KB
06. Additional-Python-Tools-Solutions.ipynb	25.5 KB
01. Introduction to pandas Series.mp4	25.0 MB
01. Introduction to pandas Series.vtt	10.8 KB
02. A Note on Completing the Upcoming Coding Exercises.html	3.0 KB
03. Working with Methods in Python - Part I.mp4	13.2 MB
03. Working with Methods in Python - Part I.vtt	7.2 KB
04. Working with Methods in Python - Part II.mp4	9.0 MB
04. Working with Methods in Python - Part II.vtt	3.9 KB
05. Parameters and Arguments in pandas.mp4	21.1 MB
05. Parameters and Arguments in pandas.vtt	5.8 KB
06. Using .unique() and .nunique().mp4	24.3 MB
06. Using .unique() and .nunique().vtt	5.8 KB
07. Using .sort_values().mp4	15.2 MB
07. Using .sort_values().vtt	5.6 KB
08. Introduction to pandas DataFrames - Part I.mp4	12.5 MB
08. Introduction to pandas DataFrames - Part I.vtt	7.3 KB
09. Introduction to pandas DataFrames - Part II.mp4	17.8 MB
09. Introduction to pandas DataFrames - Part II.vtt	8.0 KB
10. pandas DataFrames - Common Attributes.mp4	25.6 MB
10. pandas DataFrames - Common Attributes.vtt	6.6 KB
11. Data Selection in pandas DataFrames.mp4	37.3 MB
11. Data Selection in pandas DataFrames.vtt	10.5 KB
12. pandas DataFrames - Indexing with .iloc[].mp4	32.2 MB
12. pandas DataFrames - Indexing with .iloc[].vtt	8.3 KB
13. pandas DataFrames - Indexing with .loc[].mp4	20.7 MB
13. pandas DataFrames - Indexing with .loc[].vtt	5.6 KB
01. Lending-company.csv	112.4 KB
01. Location.csv	13.5 KB
01. pandas-Fundamentals-Exercises.ipynb	31.0 KB
01. pandas-Fundamentals-Lectures.ipynb	21.3 KB
01. pandas-Fundamentals-Solutions.ipynb	118.3 KB
01. Region.csv	10.2 KB
01. Sales-products.csv	152.3 KB
13. Lending-company.csv	112.4 KB
13. Location.csv	13.5 KB
13. pandas-Fundamentals-Exercises.ipynb	31.0 KB
13. pandas-Fundamentals-Lectures.ipynb	21.3 KB
13. pandas-Fundamentals-Solutions.ipynb	118.3 KB
13. Region.csv	10.2 KB
13. Sales-products.csv	152.3 KB
01. Bonus Lecture Next Steps.html	4.3 KB
01. 365-Data-Science-Data-Science-Interview-Questions-Guide.pdf	15.6 MB

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