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Udemy Complete Data Science Machine Learning A Z with Python

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Total Size:

10.6 GB

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995E52C707E965713E15F8BE5A94177580E2717E

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fcs0310

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June 27, 2023, 1:39 p.m.

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| (Last updated: May 17, 2025, 3:17 a.m.)

File	Size
[CourseClub.Me].url	122 bytes
[FreeCourseSite.com].url	127 bytes
[GigaCourse.Com].url	49 bytes
1. Installing Anaconda Distribution for Windows.mp4	118.3 MB
2. Notebook Project Files Link regarding NumPy Python Programming Language Library.html	155 bytes
3. Installing Anaconda Distribution for MacOs.mp4	46.3 MB
4. 6 Article Advice And Links about Numpy, Numpy Pyhon.html	4.2 KB
5. Installing Anaconda Distribution for Linux.mp4	114.8 MB
1. Element Selection Operations in Pandas DataFrames Lesson 1.mp4	29.9 MB
2. Element Selection Operations in Pandas DataFrames Lesson 2.mp4	31.8 MB
3. Top Level Element Selection in Pandas DataFramesLesson 1.mp4	38.3 MB
4. Top Level Element Selection in Pandas DataFramesLesson 2.mp4	31.4 MB
5. Top Level Element Selection in Pandas DataFramesLesson 3.mp4	22.1 MB
6. Element Selection with Conditional Operations in.mp4	46.4 MB
7. Quiz.html	205 bytes
[CourseClub.Me].url	122 bytes
[FreeCourseSite.com].url	127 bytes
[GigaCourse.Com].url	49 bytes
1. Adding Columns to Pandas Data Frames.mp4	33.6 MB
2. Removing Rows and Columns from Pandas Data frames.mp4	15.6 MB
3. Null Values in Pandas Dataframes.mp4	67.0 MB
4. Dropping Null Values Dropna() Function.mp4	34.5 MB
5. Filling Null Values Fillna() Function.mp4	51.6 MB
6. Setting Index in Pandas DataFrames.mp4	39.7 MB
7. Quiz.html	205 bytes
1. Multi-Index and Index Hierarchy in Pandas DataFrames.mp4	42.7 MB
2. Element Selection in Multi-Indexed DataFrames.mp4	24.6 MB
3. Selecting Elements Using the xs() Function in Multi-Indexed DataFrames.mp4	31.3 MB
4. Quiz.html	205 bytes
1. Concatenating Pandas Dataframes Concat Function.mp4	63.8 MB
2. Merge Pandas Dataframes Merge() Function Lesson 1.mp4	57.3 MB
3. Merge Pandas Dataframes Merge() Function Lesson 2.mp4	30.5 MB
4. Merge Pandas Dataframes Merge() Function Lesson 3.mp4	60.2 MB
5. Merge Pandas Dataframes Merge() Function Lesson 4.mp4	40.7 MB
6. Joining Pandas Dataframes Join() Function.mp4	56.1 MB
7. Quiz.html	205 bytes
1. Loading a Dataset from the Seaborn Library.mp4	37.7 MB
10. Quiz.html	205 bytes
2. Examining the Data Set 1.mp4	42.9 MB
3. Aggregation Functions in Pandas DataFrames.mp4	90.7 MB
4. Examining the Data Set 2.mp4	46.6 MB
5. Coordinated Use of Grouping and Aggregation Functions in Pandas Dataframes.mp4	88.1 MB
6. Advanced Aggregation Functions Aggregate() Function.mp4	29.2 MB
7. Advanced Aggregation Functions Filter() Function.mp4	24.4 MB
8. Advanced Aggregation Functions Transform() Function.mp4	47.1 MB
9. Advanced Aggregation Functions Apply() Function.mp4	41.4 MB
1. Examining the Data Set 3.mp4	39.1 MB
2. Pivot Tables in Pandas Library.mp4	54.2 MB
3. Quiz.html	205 bytes
1. Accessing and Making Files Available.mp4	34.6 MB
2. Data Entry with Csv and Txt Files.mp4	64.3 MB
3. Data Entry with Excel Files.mp4	21.8 MB
4. Outputting as an CSV Extension.mp4	35.7 MB
5. Outputting as an Excel File.mp4	19.7 MB
6. Quiz.html	205 bytes
1. Data Visualisation - Matplotlib Files.html	170 bytes
2. Data Visualisation - Seaborn Files.html	170 bytes
3. Data Visualisation - Geoplotlib.html	168 bytes
1. Introduction to Data Visualization with Python.mp4	12.8 MB
2. FAQ regarding Data Visualization, Python.html	8.6 KB
1. Data Types in Python.mp4	47.1 MB
10. Exercise - Solution in Python.mp4	51.9 MB
11. Quiz.html	205 bytes
2. Operators in Python.mp4	35.7 MB
3. Conditionals in Python.mp4	41.2 MB
4. Loops in Python.mp4	58.8 MB
5. Lists, Tuples, Dictionaries and Sets in pyhton.mp4	75.3 MB
6. Data Type Operators and Methods in Python.mp4	43.9 MB
7. Modules in Python.mp4	23.9 MB
8. Functions in Python.mp4	28.9 MB
9. Exercise - Analyse in Python.mp4	8.5 MB
1. Introduction to NumPy Library.mp4	45.3 MB
2. The Power of NumPy.mp4	59.9 MB
3. Quiz.html	205 bytes
1. Logic of Object Oriented Programming.mp4	17.4 MB
2. Constructor in Object Oriented Programming (OOP).mp4	35.8 MB
3. Methods in Object Oriented Programming (OOP).mp4	25.1 MB
4. Inheritance in Object Oriented Programming (OOP).mp4	34.6 MB
5. Overriding and Overloading in Object Oriented Programming (OOP).mp4	62.7 MB
6. Quiz.html	205 bytes
1. What is Matplotlib.mp4	19.1 MB
10. Quiz.html	205 bytes
2. Using Pyplot.mp4	28.2 MB
3. Pyplot – Pylab - Matplotlib.mp4	28.4 MB
4. Figure, Subplot and Axex.mp4	69.9 MB
5. Figure Customization.mp4	63.3 MB
6. Plot Customization.mp4	27.4 MB
7. Grid, Spines, Ticks.mp4	23.9 MB
8. Basic Plots in Matplotlib I.mp4	111.2 MB
9. Basic Plots in Matplotlib II.mp4	54.8 MB
1. What is Seaborn.mp4	13.6 MB
2. Controlling Figure Aesthetics in Seaborn.mp4	41.8 MB
3. Example in Seaborn.mp4	54.9 MB
4. Color Palettes in Seaborn.mp4	48.3 MB
5. Basic Plots in Seaborn.mp4	98.8 MB
6. Multi-Plots in Seaborn.mp4	43.0 MB
7. Regression Plots and Squarify in Seaborn.mp4	60.1 MB
8. Quiz.html	205 bytes
1. What is Geoplotlib.mp4	34.2 MB
2. Example - 1.mp4	38.9 MB
3. Example - 2.mp4	81.1 MB
4. Example - 3.mp4	51.3 MB
5. Quiz.html	205 bytes
1. What is Machine Learning.mp4	27.6 MB
2. Machine Learning Terminology.mp4	14.0 MB
3. Machine Learning Project Files.html	254 bytes
4. FAQ regarding Python.html	6.2 KB
5. FAQ regarding Machine Learning.html	6.6 KB
6. Quiz.html	205 bytes
1. Classification vs Regression in Machine Learning.mp4	19.9 MB
2. Machine Learning Model Performance Evaluation Classification Error Metrics.mp4	100.3 MB
3. Evaluating Performance Regression Error Metrics in Python.mp4	45.7 MB
4. Machine Learning With Python.mp4	92.2 MB
5. Quiz.html	205 bytes
[CourseClub.Me].url	122 bytes
[FreeCourseSite.com].url	127 bytes
[GigaCourse.Com].url	49 bytes
1. What is Supervised Learning in Machine Learning.mp4	31.7 MB
2. Quiz.html	205 bytes
1. Linear Regression Algorithm Theory in Machine Learning A-Z.mp4	34.1 MB
2. Linear Regression Algorithm With Python Part 1.mp4	76.2 MB
3. Linear Regression Algorithm With Python Part 2.mp4	106.9 MB
4. Linear Regression Algorithm With Python Part 3.mp4	70.3 MB
5. Linear Regression Algorithm With Python Part 4.mp4	90.0 MB
1. What is Bias Variance Trade-Off.mp4	55.0 MB
2. Quiz.html	205 bytes
1. What is Logistic Regression Algorithm in Machine Learning.mp4	27.8 MB
2. Logistic Regression Algorithm with Python Part 1.mp4	72.2 MB
3. Logistic Regression Algorithm with Python Part 2.mp4	81.5 MB
4. Logistic Regression Algorithm with Python Part 3.mp4	47.3 MB
5. Logistic Regression Algorithm with Python Part 4.mp4	47.2 MB
6. Logistic Regression Algorithm with Python Part 5.mp4	39.3 MB
7. Quiz.html	205 bytes
1. Creating NumPy Array with The Array() Function.mp4	29.5 MB
10. Quiz.html	205 bytes
2. Creating NumPy Array with Zeros() Function.mp4	24.1 MB
3. Creating NumPy Array with Ones() Function.mp4	15.9 MB
4. Creating NumPy Array with Full() Function.mp4	11.2 MB
5. Creating NumPy Array with Arange() Function.mp4	12.1 MB
6. Creating NumPy Array with Eye() Function.mp4	12.6 MB
7. Creating NumPy Array with Linspace() Function.mp4	7.3 MB
8. Creating NumPy Array with Random() Function.mp4	43.3 MB
9. Properties of NumPy Array.mp4	22.0 MB
1. K-Fold Cross-Validation Theory.mp4	17.4 MB
2. K-Fold Cross-Validation with Python.mp4	34.7 MB
1. K Nearest Neighbors Algorithm Theory.mp4	28.7 MB
2. K Nearest Neighbors Algorithm with Python Part 1.mp4	35.0 MB
3. K Nearest Neighbors Algorithm with Python Part 2.mp4	59.4 MB
4. K Nearest Neighbors Algorithm with Python Part 3.mp4	31.4 MB
5. Quiz.html	205 bytes
1. Hyperparameter Optimization Theory.mp4	33.1 MB
2. Hyperparameter Optimization with Python.mp4	47.5 MB
1. Decision Tree Algorithm Theory.mp4	35.8 MB
2. Decision Tree Algorithm with Python Part 1.mp4	31.5 MB
3. Decision Tree Algorithm with Python Part 2.mp4	48.9 MB
4. Decision Tree Algorithm with Python Part 3.mp4	14.7 MB
5. Decision Tree Algorithm with Python Part 4.mp4	42.5 MB
6. Decision Tree Algorithm with Python Part 5.mp4	32.7 MB
7. Quiz.html	205 bytes
1. Random Forest Algorithm Theory.mp4	22.9 MB
2. Random Forest Algorithm with Pyhon Part 1.mp4	38.6 MB
3. Random Forest Algorithm with Pyhon Part 2.mp4	38.7 MB
1. Support Vector Machine Algorithm Theory.mp4	21.8 MB
2. Support Vector Machine Algorithm with Python Part 1.mp4	35.6 MB
3. Support Vector Machine Algorithm with Python Part 2.mp4	41.7 MB
4. Support Vector Machine Algorithm with Python Part 3.mp4	34.8 MB
5. Support Vector Machine Algorithm with Python Part 4.mp4	37.6 MB
6. Quiz.html	205 bytes
1. Unsupervised Learning Overview.mp4	16.9 MB
1. K Means Clustering Algorithm Theory.mp4	17.1 MB
2. K Means Clustering Algorithm with Python Part 1.mp4	30.0 MB
3. K Means Clustering Algorithm with Python Part 2.mp4	29.6 MB
4. K Means Clustering Algorithm with Python Part 3.mp4	27.8 MB
5. K Means Clustering Algorithm with Python Part 4.mp4	29.0 MB
6. Quiz.html	205 bytes
1. Hierarchical Clustering Algorithm Theory.mp4	28.6 MB
2. Hierarchical Clustering Algorithm with Python Part 2.mp4	35.5 MB
3. Hierarchical Clustering Algorithm with Python Part 2.mp4	28.9 MB
1. Principal Component Analysis (PCA) Theory.mp4	38.0 MB
2. Principal Component Analysis (PCA) with Python Part 1.mp4	26.0 MB
3. Principal Component Analysis (PCA) with Python Part 2.mp4	8.4 MB
4. Principal Component Analysis (PCA) with Python Part 3.mp4	37.2 MB
1. Reshaping a NumPy Array Reshape() Function.mp4	26.2 MB
2. Identifying the Largest Element of a Numpy Array.mp4	15.1 MB
3. Detecting Least Element of Numpy Array Min(), Ar.mp4	10.2 MB
4. Concatenating Numpy Arrays Concatenate() Functio.mp4	38.4 MB
5. Splitting One-Dimensional Numpy Arrays The Split.mp4	20.9 MB
6. Splitting Two-Dimensional Numpy Arrays Split(),.mp4	35.7 MB
7. Sorting Numpy Arrays Sort() Function.mp4	17.0 MB
8. Quiz.html	205 bytes
1. What is the Recommender System Part 1.mp4	23.0 MB
2. What is the Recommender System Part 2.mp4	18.0 MB
1. What is Kaggle.mp4	129.7 MB
2. FAQ about Kaggle.html	10.9 KB
3. Registering on Kaggle and Member Login Procedures.mp4	43.5 MB
4. Project Link File - Hearth Attack Prediction Project, Machine Learning.html	97 bytes
5. Getting to Know the Kaggle Homepage.mp4	122.9 MB
6. quiz.html	205 bytes
1. Competitions on Kaggle Lesson 1.mp4	188.2 MB
2. Competitions on Kaggle Lesson 2.mp4	191.7 MB
1. Datasets on Kaggle.mp4	133.2 MB
2. Quiz.html	205 bytes
1. Examining the Code Section in Kaggle Lesson 1.mp4	79.5 MB
2. Examining the Code Section in Kaggle Lesson 2.mp4	105.8 MB
3. Examining the Code Section in Kaggle Lesson 3.mp4	159.9 MB
4. Quiz.html	205 bytes
1. What is Discussion on Kaggle.mp4	40.6 MB
2. Quiz.html	205 bytes
1. Courses in Kaggle.mp4	52.1 MB
2. Ranking Among Users on Kaggle.mp4	107.0 MB
3. Blog and Documentation Sections.mp4	40.9 MB
4. Quiz.html	205 bytes
1. User Page Review on Kaggle.mp4	81.5 MB
2. Treasure in The Kaggle.mp4	74.6 MB
3. Publishing Notebooks on Kaggle.mp4	38.2 MB
4. What Should Be Done to Achieve Success in Kaggle.mp4	58.5 MB
5. Quiz.html	205 bytes
1. First Step to the Hearth Attack Prediction Project.mp4	117.1 MB
2. FAQ about Machine Learning, Data Science.html	15.3 KB
3. Notebook Design to be Used in the Project.mp4	104.9 MB
4. Project Link File - Hearth Attack Prediction Project, Machine Learning.html	108 bytes
5. Examining the Project Topic.mp4	76.5 MB
6. Recognizing Variables In Dataset.mp4	126.9 MB
7. Quiz.html	205 bytes
1. Required Python Libraries.mp4	63.6 MB
2. Loading the Statistics Dataset in Data Science.mp4	10.0 MB
3. Initial analysis on the dataset.mp4	64.0 MB
4. Quiz.html	205 bytes
1. Indexing Numpy Arrays,.mp4	26.6 MB
2. Slicing One-Dimensional Numpy Arrays.mp4	22.3 MB
3. Slicing Two-Dimensional Numpy Arrays.mp4	34.3 MB
4. Assigning Value to One-Dimensional Arrays.mp4	18.2 MB
5. Assigning Value to Two-Dimensional Array.mp4	35.4 MB
6. Fancy Indexing of One-Dimensional Arrrays.mp4	20.5 MB
7. Fancy Indexing of Two-Dimensional Arrrays.mp4	45.7 MB
8. Combining Fancy Index with Normal Indexing.mp4	12.7 MB
9. Combining Fancy Index with Normal Slicing.mp4	16.5 MB
1. Examining Missing Values.mp4	45.8 MB
2. Examining Unique Values.mp4	44.5 MB
3. Separating variables (Numeric or Categorical).mp4	15.8 MB
4. Examining Statistics of Variables.mp4	91.4 MB
5. Quiz.html	205 bytes
1. Numeric Variables (Analysis with Distplot) Lesson 1.mp4	80.4 MB
2. Numeric Variables (Analysis with Distplot) Lesson 2.mp4	19.7 MB
3. Categoric Variables (Analysis with Pie Chart) Lesson 1.mp4	74.7 MB
4. Categoric Variables (Analysis with Pie Chart) Lesson 2.mp4	84.1 MB
5. Examining the Missing Data According to the Analysis Result.mp4	53.8 MB
6. Quiz.html	205 bytes
1. Numeric Variables – Target Variable (Analysis with FacetGrid) Lesson 1.mp4	49.4 MB
10. Numerical - Categorical Variables (Analysis with Swarm Plot) Lesson 2.mp4	68.1 MB
11. Numerical - Categorical Variables (Analysis with Box Plot) Lesson 1.mp4	38.1 MB
12. Numerical - Categorical Variables (Analysis with Box Plot) Lesson 2.mp4	35.5 MB
13. Relationships between variables (Analysis with Heatmap) Lesson 1.mp4	36.4 MB
14. Relationships between variables (Analysis with Heatmap) Lesson 2.mp4	90.7 MB
15. Quiz.html	205 bytes
2. Numeric Variables – Target Variable (Analysis with FacetGrid) Lesson 2.mp4	35.6 MB
3. Categoric Variables – Target Variable (Analysis with Count Plot) Lesson 1.mp4	24.1 MB
4. Categoric Variables – Target Variable (Analysis with Count Plot) Lesson 2.mp4	56.3 MB
5. Examining Numeric Variables Among Themselves (Analysis with Pair Plot) Lesson 1.mp4	28.3 MB
6. Examining Numeric Variables Among Themselves (Analysis with Pair Plot) Lesson 2.mp4	47.1 MB
7. Feature Scaling with the Robust Scaler Method.mp4	35.2 MB
8. Creating a New DataFrame with the Melt() Function.mp4	52.9 MB
9. Numerical - Categorical Variables (Analysis with Swarm Plot) Lesson 1.mp4	41.7 MB
1. Dropping Columns with Low Correlation.mp4	26.8 MB
10. Feature Scaling with the Robust Scaler Method for Machine Learning Algorithms.mp4	11.4 MB
11. Separating Data into Test and Training Set.mp4	29.8 MB
12. Quiz.html	205 bytes
2. Visualizing Outliers.mp4	34.9 MB
3. Dealing with Outliers – Trtbps Variable Lesson 1.mp4	42.8 MB
4. Dealing with Outliers – Trtbps Variable Lesson 2.mp4	43.9 MB
5. Dealing with Outliers – Thalach Variable.mp4	36.2 MB
6. Dealing with Outliers – Oldpeak Variable.mp4	36.1 MB
7. Determining Distributions of Numeric Variables.mp4	25.2 MB
8. Transformation Operations on Unsymmetrical Data.mp4	24.0 MB
9. Applying One Hot Encoding Method to Categorical Variables.mp4	24.1 MB
1. Logistic Regression.mp4	29.3 MB
2. Cross Validation.mp4	30.2 MB
3. Roc Curve and Area Under Curve (AUC).mp4	41.7 MB
4. Hyperparameter Optimization (with GridSearchCV).mp4	58.8 MB
5. Decision Tree Algorithm.mp4	25.7 MB
6. Support Vector Machine Algorithm.mp4	24.5 MB
7. Random Forest Algorithm.mp4	29.8 MB
8. Hyperparameter Optimization (with GridSearchCV).mp4	52.7 MB
9. Quiz.html	205 bytes
1. Project Conclusion and Sharing.mp4	28.7 MB
2. Quiz.html	205 bytes
1. Complete Data Science & Machine Learning A-Z with Python.html	266 bytes
1. Operations with Comparison Operators.mp4	21.1 MB
2. Arithmetic Operations in Numpy.mp4	71.8 MB
3. Statistical Operations in Numpy.mp4	32.0 MB
4. Solving Second-Degree Equations with NumPy.mp4	24.2 MB
1. Introduction to Pandas Library.mp4	33.9 MB
2. Pandas Project Files Link.html	180 bytes
3. Quiz.html	205 bytes
1. Creating a Pandas Series with a List.mp4	39.2 MB
2. Creating a Pandas Series with a Dictionary.mp4	18.3 MB
3. Creating Pandas Series with NumPy Array.mp4	12.0 MB
4. Object Types in Series.mp4	19.6 MB
5. Examining the Primary Features of the Pandas Seri.mp4	18.9 MB
6. Most Applied Methods on Pandas Series.mp4	48.2 MB
7. Indexing and Slicing Pandas Series.mp4	29.9 MB
8. Quiz.html	205 bytes
1. Creating Pandas DataFrame with List.mp4	22.6 MB
2. Creating Pandas DataFrame with NumPy Array.mp4	12.1 MB
3. Creating Pandas DataFrame with Dictionary.mp4	15.8 MB
4. Examining the Properties of Pandas DataFrames.mp4	25.9 MB
5. Quiz.html	205 bytes

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