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Language:
English
Total Size:
9.1 GB
Info Hash:
2573DF0A2B891C606621FA656140359C74749838
Added By:
Added:
July 2, 2023, 12:08 a.m.
Stats:
|
(Last updated: May 20, 2025, 6:45 a.m.)
| File | Size |
|---|---|
| 2. Competitions on Kaggle Lesson 2.mp4 | 191.7 MB |
| TutsNode.net.txt | 63 bytes |
| 2. FAQ about Machine Learning, Data Science.html | 15.3 KB |
| 2. Notebook Project Files Link regarding NumPy Python Programming Language Library.html | 155 bytes |
| 2. FAQ about Kaggle.html | 10.9 KB |
| 5. FAQ regarding Machine Learning.html | 6.6 KB |
| 4. FAQ regarding Python.html | 6.2 KB |
| 4. 6 Article Advice And Links about Numpy, Numpy Pyhon.html | 4.2 KB |
| [TGx]Downloaded from torrentgalaxy.to .txt | 585 bytes |
| 3. Quiz.html | 205 bytes |
| 1. Machine Learning & Data Science with Kaggle, Pandas , Numpy.html | 266 bytes |
| 3. Machine Learning Project Files.html | 254 bytes |
| 10. Quiz.html | 205 bytes |
| 8. Quiz.html | 205 bytes |
| 3. Quiz.html | 205 bytes |
| 8. Quiz.html | 205 bytes |
| 5. Quiz.html | 205 bytes |
| 7. Quiz.html | 205 bytes |
| 7. Quiz.html | 205 bytes |
| 4. Quiz.html | 205 bytes |
| 7. Quiz.html | 205 bytes |
| 10. Quiz.html | 205 bytes |
| 3. Quiz.html | 205 bytes |
| 6. Quiz.html | 205 bytes |
| 5. Quiz.html | 205 bytes |
| 2. Quiz.html | 205 bytes |
| 2. Quiz.html | 205 bytes |
| 7. Quiz.html | 205 bytes |
| 5. Quiz.html | 205 bytes |
| 7. Quiz.html | 205 bytes |
| 6. Quiz.html | 205 bytes |
| 2. Quiz.html | 205 bytes |
| 6. Quiz.html | 205 bytes |
| 4. Quiz.html | 205 bytes |
| 3. Quiz.html | 205 bytes |
| 6. Quiz.html | 205 bytes |
| 3. Quiz.html | 205 bytes |
| 2. Quiz.html | 205 bytes |
| 4. Quiz.html | 205 bytes |
| 2. Quiz.html | 205 bytes |
| 4. Quiz.html | 205 bytes |
| 5. Quiz.html | 205 bytes |
| 2. Pandas Project Files Link.html | 180 bytes |
| 7. Quiz.html | 205 bytes |
| 4. Quiz.html | 205 bytes |
| 5. Quiz.html | 205 bytes |
| 6. Quiz.html | 205 bytes |
| 15. Quiz.html | 205 bytes |
| 12. Quiz.html | 205 bytes |
| 9. Quiz.html | 205 bytes |
| 2. Quiz.html | 205 bytes |
| 4. Project Link File - Hearth Attack Prediction Project, Machine Learning.html | 108 bytes |
| 4. Project Link File - Hearth Attack Prediction Project, Machine Learning.html | 108 bytes |
| 0 | 241.7 KB |
| 1. Competitions on Kaggle Lesson 1.mp4 | 188.2 MB |
| 1 | 821.5 KB |
| 3. Examining the Code Section in Kaggle Lesson 3.mp4 | 159.8 MB |
| 2 | 181.0 KB |
| 1. Datasets on Kaggle.mp4 | 133.2 MB |
| 3 | 813.9 KB |
| 1. What is Kaggle.mp4 | 129.7 MB |
| 4 | 256.3 KB |
| 6. Recognizing Variables In Dataset.mp4 | 126.9 MB |
| 5 | 126.5 KB |
| 5. Getting to Know the Kaggle Homepage.mp4 | 122.9 MB |
| 6 | 120.6 KB |
| 1. Installing Anaconda Distribution for Windows.mp4 | 118.3 MB |
| 7 | 711.8 KB |
| 1. First Step to the Project.mp4 | 117.2 MB |
| 8 | 832.8 KB |
| 5. Installing Anaconda Distribution for Linux.mp4 | 114.8 MB |
| 9 | 214.5 KB |
| 2. Ranking Among Users on Kaggle.mp4 | 107.0 MB |
| 10 | 2.2 KB |
| 3. Linear Regression Algorithm With Python Part 2.mp4 | 106.9 MB |
| 11 | 59.1 KB |
| 2. Examining the Code Section in Kaggle Lesson 2.mp4 | 105.8 MB |
| 12 | 199.3 KB |
| 3. Notebook Design to be Used in the Project.mp4 | 105.0 MB |
| 13 | 35.9 KB |
| 2. Machine Learning Model Performance Evaluation Classification Error Metrics.mp4 | 100.3 MB |
| 14 | 731.5 KB |
| 4. Machine Learning With Python.mp4 | 92.3 MB |
| 15 | 757.9 KB |
| 4. Examining Statistics of Variables.mp4 | 91.4 MB |
| 16 | 636.0 KB |
| 3. Aggregation Functions in Pandas DataFrames.mp4 | 90.7 MB |
| 17 | 300.2 KB |
| 14. Relationships between variables (Analysis with Heatmap) Lesson 2.mp4 | 90.7 MB |
| 18 | 352.2 KB |
| 5. Linear Regression Algorithm With Python Part 4.mp4 | 90.0 MB |
| 19 | 5.1 KB |
| 5. Coordinated Use of Grouping and Aggregation Functions in Pandas Dataframes.mp4 | 88.1 MB |
| 20 | 903.6 KB |
| 4. Categoric Variables (Analysis with Pie Chart) Lesson 2.mp4 | 84.0 MB |
| 21 | 986.5 KB |
| 1. User Page Review on Kaggle.mp4 | 81.6 MB |
| 22 | 438.4 KB |
| 3. Logistic Regression Algorithm with Python Part 2.mp4 | 81.5 MB |
| 23 | 556.6 KB |
| 1. Numeric Variables (Analysis with Distplot) Lesson 1.mp4 | 80.4 MB |
| 24 | 612.6 KB |
| 1. Examining the Code Section in Kaggle Lesson 1.mp4 | 79.5 MB |
| 25 | 464.9 KB |
| 5. Examining the Project Topic.mp4 | 76.5 MB |
| 26 | 485.1 KB |
| 2. Linear Regression Algorithm With Python Part 1.mp4 | 76.2 MB |
| 27 | 844.4 KB |
| 3. Categoric Variables (Analysis with Pie Chart) Lesson 1.mp4 | 74.8 MB |
| 28 | 240.4 KB |
| 2. Treasure in The Kaggle.mp4 | 74.7 MB |
| 29 | 350.4 KB |
| 2. Logistic Regression Algorithm with Python Part 1.mp4 | 72.2 MB |
| 30 | 790.2 KB |
| 2. Arithmetic Operations in Numpy.mp4 | 71.9 MB |
| 31 | 129.9 KB |
| 4. Linear Regression Algorithm With Python Part 3.mp4 | 70.3 MB |
| 32 | 734.3 KB |
| 10. Numerical - Categorical Variables (Analysis with Swarm Plot) Lesson 2.mp4 | 68.1 MB |
| 33 | 949.3 KB |
| 3. Null Values in Pandas Dataframes.mp4 | 67.0 MB |
| 34 | 50.8 KB |
| 2. Data Entry with Csv and Txt Files.mp4 | 64.4 MB |
| 35 | 659.1 KB |
| 3. Initial analysis on the dataset.mp4 | 64.0 MB |
| 36 | 19.4 KB |
| 1. Concatenating Pandas Dataframes Concat Function.mp4 | 63.9 MB |
| 37 | 125.5 KB |
| 1. Required Python Libraries.mp4 | 63.6 MB |
| 38 | 438.0 KB |
| 4. Merge Pandas Dataframes Merge() Function Lesson 3.mp4 | 60.1 MB |
| 39 | 883.1 KB |
| 2. The Power of NumPy.mp4 | 59.9 MB |
| 40 | 137.8 KB |
| 3. K Nearest Neighbors Algorithm with Python Part 2.mp4 | 59.4 MB |
| 41 | 623.9 KB |
| 4. Hyperparameter Optimization (with GridSearchCV).mp4 | 58.8 MB |
| 42 | 237.4 KB |
| 4. What Should Be Done to Achieve Success in Kaggle.mp4 | 58.4 MB |
| 43 | 594.2 KB |
| 2. Merge Pandas Dataframes Merge() Function Lesson 1.mp4 | 57.3 MB |
| 44 | 717.7 KB |
| 4. Categoric Variables – Target Variable (Analysis with Count Plot) Lesson 2.mp4 | 56.3 MB |
| 45 | 741.4 KB |
| 6. Joining Pandas Dataframes Join() Function.mp4 | 56.1 MB |
| 46 | 971.3 KB |
| 1. What is Bias Variance Trade-Off.mp4 | 55.0 MB |
| 47 | 983.0 KB |
| 2. Pivot Tables in Pandas Library.mp4 | 54.2 MB |
| 48 | 787.8 KB |
| 5. Examining the Missing Data According to the Analysis Result.mp4 | 53.8 MB |
| 49 | 223.0 KB |
| 8. Creating a New DataFrame with the Melt() Function.mp4 | 52.9 MB |
| 50 | 120.7 KB |
| 8. Hyperparameter Optimization (with GridSearchCV).mp4 | 52.7 MB |
| 51 | 334.2 KB |
| 1. Courses in Kaggle.mp4 | 52.2 MB |
| 52 | 855.0 KB |
| 5. Filling Null Values Fillna() Function.mp4 | 51.6 MB |
| 53 | 395.3 KB |
| 1. Numeric Variables – Target Variable (Analysis with FacetGrid) Lesson 1.mp4 | 49.3 MB |
| 54 | 678.8 KB |
| 3. Decision Tree Algorithm with Python Part 2.mp4 | 49.0 MB |
| 55 | 31.5 KB |
| 6. Most Applied Methods on Pandas Series.mp4 | 48.2 MB |
| 56 | 826.0 KB |
| 2. Hyperparameter Optimization with Python.mp4 | 47.5 MB |
| 57 | 546.1 KB |
| 4. Support Vector Machine Algorithm with Python Part 3.mp4 | 47.3 MB |
| 58 | 670.5 KB |
| 5. Logistic Regression Algorithm with Python Part 4.mp4 | 47.2 MB |
| 59 | 855.9 KB |
| 6. Examining Numeric Variables Among Themselves (Analysis with Pair Plot) Lesson 2.mp4 | 47.2 MB |
| 60 | 861.6 KB |
| 8. Advanced Aggregation Functions Transform() Function.mp4 | 47.1 MB |
| 61 | 925.7 KB |
| 4. Examining the Data Set 2.mp4 | 46.6 MB |
| 62 | 442.6 KB |
| 6. Element Selection with Conditional Operations in.mp4 | 46.4 MB |
| 63 | 647.6 KB |
| 3. Installing Anaconda Distribution for MacOs.mp4 | 46.3 MB |
| 64 | 671.0 KB |
| 1. Examining Missing Values.mp4 | 45.8 MB |
| 65 | 224.7 KB |
| 7. Fancy Indexing of Two-Dimensional Arrrays.mp4 | 45.7 MB |
| 66 | 283.6 KB |
| 3. Evaluating Performance Regression Error Metrics in Python.mp4 | 45.7 MB |
| 67 | 296.8 KB |
| 1. Introduction to NumPy Library.mp4 | 45.3 MB |
| 68 | 714.8 KB |
| 2. Examining Unique Values.mp4 | 44.6 MB |
| 69 | 449.2 KB |
| 4. Dealing with Outliers – Trtbps Variable Lesson 2.mp4 | 43.9 MB |
| 70 | 88.3 KB |
| 3. Registering on Kaggle and Member Login Procedures.mp4 | 43.5 MB |
| 71 | 461.2 KB |
| 8. Creating NumPy Array with Random() Function.mp4 | 43.3 MB |
| 72 | 720.3 KB |
| 2. Examining the Data Set 1.mp4 | 42.9 MB |
| 73 | 124.6 KB |
| 3. Dealing with Outliers – Trtbps Variable Lesson 1.mp4 | 42.8 MB |
| 74 | 167.5 KB |
| 1. Multi-Index and Index Hierarchy in Pandas DataFrames.mp4 | 42.7 MB |
| 75 | 348.6 KB |
| 5. Decision Tree Algorithm with Python Part 4.mp4 | 42.5 MB |
| 76 | 517.6 KB |
| 3. Support Vector Machine Algorithm with Python Part 2.mp4 | 41.7 MB |
| 77 | 288.1 KB |
| 9. Numerical - Categorical Variables (Analysis with Swarm Plot) Lesson 1.mp4 | 41.7 MB |
| 78 | 305.5 KB |
| 3. Roc Curve and Area Under Curve (AUC).mp4 | 41.7 MB |
| 79 | 323.0 KB |
| 9. Advanced Aggregation Functions Apply() Function.mp4 | 41.4 MB |
| 80 | 586.6 KB |
| 3. Blog and Documentation Sections.mp4 | 40.9 MB |
| 81 | 92.7 KB |
| 5. Merge Pandas Dataframes Merge() Function Lesson 4.mp4 | 40.7 MB |
| 82 | 308.3 KB |
| 1. What is Discussion on Kaggle.mp4 | 40.6 MB |
| 83 | 359.9 KB |
| 6. Setting Index in Pandas DataFrames.mp4 | 39.7 MB |
| 84 | 306.3 KB |
| 6. Logistic Regression Algorithm with Python Part 5.mp4 | 39.4 MB |
| 85 | 658.6 KB |
| 1. Creating a Pandas Series with a List.mp4 | 39.2 MB |
| 86 | 819.2 KB |
| 1. Examining the Data Set 3.mp4 | 39.1 MB |
| 87 | 900.1 KB |
| 3. Random Forest Algorithm with Pyhon Part 2.mp4 | 38.7 MB |
| 88 | 270.0 KB |
| 2. Random Forest Algorithm with Pyhon Part 1.mp4 | 38.6 MB |
| 89 | 418.6 KB |
| 4. Concatenating Numpy Arrays Concatenate() Function.mp4 | 38.4 MB |
| 90 | 638.4 KB |
| 3. Top Level Element Selection in Pandas DataFramesLesson 1.mp4 | 38.3 MB |
| 91 | 709.9 KB |
| 3. Publishing Notebooks on Kaggle.mp4 | 38.2 MB |
| 92 | 810.0 KB |
| 11. Numerical - Categorical Variables (Analysis with Box Plot) Lesson 1.mp4 | 38.1 MB |
| 93 | 955.4 KB |
| 1. Principal Component Analysis (PCA) Theory.mp4 | 38.0 MB |
| 94 | 49.1 KB |
| 1. Loading a Dataset from the Seaborn Library.mp4 | 37.7 MB |
| 95 | 288.7 KB |
| 5. Support Vector Machine Algorithm with Python Part 4.mp4 | 37.6 MB |
| 96 | 453.1 KB |
| 4. Principal Component Analysis (PCA) with Python Part 3.mp4 | 37.3 MB |
| 97 | 744.2 KB |
| 13. Relationships between variables (Analysis with Heatmap) Lesson 1.mp4 | 36.4 MB |
| 98 | 646.8 KB |
| 5. Dealing with Outliers – Thalach Variable.mp4 | 36.2 MB |
| 99 | 789.3 KB |
| 6. Dealing with Outliers – Oldpeak Variable.mp4 | 36.1 MB |
| 100 | 938.9 KB |
| 1. Decision Tree Algorithm Theory.mp4 | 35.8 MB |
| 101 | 249.1 KB |
| 6. Splitting Two-Dimensional Numpy Arrays Split(),.mp4 | 35.7 MB |
| 102 | 286.5 KB |
| 4. Outputting as an CSV Extension.mp4 | 35.7 MB |
| 103 | 298.0 KB |
| 2. Numeric Variables – Target Variable (Analysis with FacetGrid) Lesson 2.mp4 | 35.6 MB |
| 104 | 389.3 KB |
| 2. Support Vector Machine Algorithm with Python Part 1.mp4 | 35.6 MB |
| 105 | 445.7 KB |
| 2. Hierarchical Clustering Algorithm with Python Part 1.mp4 | 35.5 MB |
| 106 | 496.9 KB |
| 12. Numerical - Categorical Variables (Analysis with Box Plot) Lesson 2.mp4 | 35.5 MB |
| 107 | 552.4 KB |
| 5. Assigning Value to Two-Dimensional Array.mp4 | 35.4 MB |
| 108 | 602.0 KB |
| 7. Feature Scaling with the Robust Scaler Method.mp4 | 35.2 MB |
| 109 | 824.9 KB |
| 2. K Nearest Neighbors Algorithm with Python Part 1.mp4 | 35.1 MB |
| 110 | 970.8 KB |
| 2. Visualizing Outliers.mp4 | 34.9 MB |
| 111 | 137.2 KB |
| 4. Logistic Regression Algorithm with Python Part 3.mp4 | 34.8 MB |
| 112 | 229.2 KB |
| 2. K-Fold Cross-Validation with Python.mp4 | 34.7 MB |
| 113 | 349.0 KB |
| 1. Accessing and Making Files Available.mp4 | 34.6 MB |
| 114 | 384.1 KB |
| 4. Dropping Null Values Dropna() Function.mp4 | 34.5 MB |
| 115 | 481.8 KB |
| 3. Slicing Two-Dimensional Numpy Arrays.mp4 | 34.3 MB |
| 116 | 744.1 KB |
| 1. Linear Regression Algorithm Theory in Machine Learning A-Z.mp4 | 34.1 MB |
| 117 | 958.0 KB |
| 1. Introduction to Pandas Library.mp4 | 33.9 MB |
| 118 | 76.0 KB |
| 1. Adding Columns to Pandas Data Frames.mp4 | 33.6 MB |
| 119 | 434.2 KB |
| 1. Hyperparameter Optimization Theory.mp4 | 33.1 MB |
| 120 | 874.9 KB |
| 6. Decision Tree Algorithm with Python Part 5.mp4 | 32.7 MB |
| 121 | 331.5 KB |
| 3. Statistical Operations in Numpy.mp4 | 32.0 MB |
| 122 | 21.4 KB |
| 2. Element Selection Operations in Pandas DataFrames Lesson 2.mp4 | 31.8 MB |
| 123 | 178.3 KB |
| 1. What is Supervised Learning in Machine Learning.mp4 | 31.7 MB |
| 124 | 320.3 KB |
| 2. Decision Tree Algorithm with Python Part 1.mp4 | 31.5 MB |
| 125 | 467.7 KB |
| 4. Top Level Element Selection in Pandas DataFramesLesson 2.mp4 | 31.4 MB |
| 126 | 592.9 KB |
| 4. K Nearest Neighbors Algorithm with Python Part 3.mp4 | 31.4 MB |
| 127 | 623.1 KB |
| 3. Selecting Elements Using the xs() Function in Multi-Indexed DataFrames.mp4 | 31.3 MB |
| 128 | 733.9 KB |
| 3. Merge Pandas Dataframes Merge() Function Lesson 2.mp4 | 30.5 MB |
| 129 | 495.7 KB |
| 2. Cross Validation.mp4 | 30.2 MB |
| 130 | 811.8 KB |
| 2. K Means Clustering Algorithm with Python Part 1.mp4 | 29.9 MB |
| 131 | 64.6 KB |
| 7. Indexing and Slicing Pandas Series.mp4 | 29.9 MB |
| 132 | 89.7 KB |
| 1. Element Selection Operations in Pandas DataFrames Lesson 1.mp4 | 29.9 MB |
| 133 | 120.0 KB |
| 7. Random Forest Algorithm.mp4 | 29.8 MB |
| 134 | 228.4 KB |
| 11. Separating Data into Test and Training Set.mp4 | 29.8 MB |
| 135 | 248.0 KB |
| 3. K Means Clustering Algorithm with Python Part 2.mp4 | 29.7 MB |
| 136 | 356.3 KB |
| 1. Creating NumPy Array with The Array() Function.mp4 | 29.5 MB |
| 137 | 525.2 KB |
| 1. Logistic Regression.mp4 | 29.3 MB |
| 138 | 673.5 KB |
| 6. Advanced Aggregation Functions Aggregate() Function.mp4 | 29.2 MB |
| 139 | 785.6 KB |
| 5. K Means Clustering Algorithm with Python Part 4.mp4 | 29.0 MB |
| 140 | 997.7 KB |
| 3. Hierarchical Clustering Algorithm with Python Part 2.mp4 | 28.9 MB |
| 141 | 102.5 KB |
| 1. K Nearest Neighbors Algorithm Theory.mp4 | 28.7 MB |
| 142 | 337.9 KB |
| 1. Project Conclusion and Sharing.mp4 | 28.7 MB |
| 143 | 354.9 KB |
| 1. Hierarchical Clustering Algorithm Theory.mp4 | 28.6 MB |
| 144 | 443.2 KB |
| 5. Examining Numeric Variables Among Themselves (Analysis with Pair Plot) Lesson 1.mp4 | 28.4 MB |
| 145 | 656.2 KB |
| 1. What is Logistic Regression Algorithm in Machine Learning.mp4 | 27.8 MB |
| 146 | 164.2 KB |
| 4. K Means Clustering Algorithm with Python Part 3.mp4 | 27.8 MB |
| 147 | 246.5 KB |
| 1. What is Machine Learning.mp4 | 27.6 MB |
| 148 | 431.5 KB |
| 1. Dropping Columns with Low Correlation.mp4 | 26.8 MB |
| 149 | 187.8 KB |
| 1. Indexing Numpy Arrays.mp4 | 26.6 MB |
| 150 | 409.6 KB |
| 1. Reshaping a NumPy Array Reshape() Function.mp4 | 26.2 MB |
| 151 | 869.1 KB |
| 2. Principal Component Analysis (PCA) with Python Part 1.mp4 | 26.0 MB |
| 152 | 1002.7 KB |
| 4. Examining the Properties of Pandas DataFrames.mp4 | 25.9 MB |
| 153 | 53.6 KB |
| 5. Decision Tree Algorithm.mp4 | 25.7 MB |
| 154 | 307.3 KB |
| 7. Determining Distributions of Numeric Variables.mp4 | 25.2 MB |
| 155 | 817.3 KB |
| 2. Element Selection in Multi-Indexed DataFrames.mp4 | 24.6 MB |
| 156 | 418.4 KB |
| 6. Support Vector Machine Algorithm.mp4 | 24.5 MB |
| 157 | 513.2 KB |
| 7. Advanced Aggregation Functions Filter() Function.mp4 | 24.5 MB |
| 158 | 547.0 KB |
| 4. Solving Second-Degree Equations with NumPy.mp4 | 24.2 MB |
| 159 | 816.6 KB |
| 3. Categoric Variables – Target Variable (Analysis with Count Plot) Lesson 1.mp4 | 24.1 MB |
| 160 | 896.7 KB |
| 9. Applying One Hot Encoding Method to Categorical Variables.mp4 | 24.1 MB |
| 161 | 932.9 KB |
| 2. Creating NumPy Array with Zeros() Function.mp4 | 24.1 MB |
| 162 | 961.1 KB |
| 8. Transformation Operations on Unsymmetrical Data.mp4 | 24.0 MB |
| 163 | 2.6 KB |
| 1. What is the Recommender System Part 1.mp4 | 23.0 MB |
| 164 | 1001.6 KB |
| 1. Random Forest Algorithm Theory.mp4 | 22.9 MB |
| 165 | 112.4 KB |
| 1. Creating Pandas DataFrame with List.mp4 | 22.6 MB |
| 166 | 450.4 KB |
| 2. Slicing One-Dimensional Numpy Arrays.mp4 | 22.3 MB |
| 167 | 728.0 KB |
| 5. Top Level Element Selection in Pandas DataFramesLesson 3.mp4 | 22.1 MB |
| 168 | 941.4 KB |
| 9. Properties of NumPy Array.mp4 | 22.0 MB |
| 169 | 1012.2 KB |
| 1. Support Vector Machine Algorithm Theory.mp4 | 21.8 MB |
| 170 | 162.2 KB |
| 3. Data Entry with Excel Files.mp4 | 21.8 MB |
| 171 | 171.1 KB |
| 1. Operations with Comparison Operators.mp4 | 21.2 MB |
| 172 | 854.5 KB |
| 5. Splitting One-Dimensional Numpy Arrays The Split.mp4 | 20.9 MB |
| 173 | 91.4 KB |
| 6. Fancy Indexing of One-Dimensional Arrrays.mp4 | 20.5 MB |
| 174 | 527.8 KB |
| 1. Classification vs Regression in Machine Learning.mp4 | 19.9 MB |
| 175 | 96.5 KB |
| 5. Outputting as an Excel File.mp4 | 19.8 MB |
| 176 | 245.8 KB |
| 2. Numeric Variables (Analysis with Distplot) Lesson 2.mp4 | 19.7 MB |
| 177 | 276.2 KB |
| 4. Object Types in Series.mp4 | 19.5 MB |
| 178 | 461.5 KB |
| 5. Examining the Primary Features of the Pandas Seri.mp4 | 18.9 MB |
| 179 | 67.0 KB |
| 2. Creating a Pandas Series with a Dictionary.mp4 | 18.3 MB |
| 180 | 726.8 KB |
| 4. Assigning Value to One-Dimensional Arrays.mp4 | 18.2 MB |
| 181 | 815.7 KB |
| 2. What is the Recommender System Part 2.mp4 | 18.0 MB |
| 182 | 42.7 KB |
| 1. K-Fold Cross-Validation Theory.mp4 | 17.5 MB |
| 183 | 550.7 KB |
| 1. K Means Clustering Algorithm Theory.mp4 | 17.1 MB |
| 184 | 878.1 KB |
| 7. Sorting Numpy Arrays Sort() Function.mp4 | 17.0 MB |
| 185 | 985.8 KB |
| 1. Unsupervised Learning Overview.mp4 | 16.9 MB |
| 186 | 81.9 KB |
| 9. Combining Fancy Index with Normal Slicing.mp4 | 16.5 MB |
| 187 | 555.6 KB |
| 3. Creating NumPy Array with Ones() Function.mp4 | 15.8 MB |
| 188 | 163.3 KB |
| 3. Separating variables (Numeric or Categorical).mp4 | 15.8 MB |
| 189 | 168.4 KB |
| 3. Creating Pandas DataFrame with Dictionary.mp4 | 15.8 MB |
| 190 | 179.0 KB |
| 2. Removing Rows and Columns from Pandas Data frames.mp4 | 15.6 MB |
| 191 | 439.4 KB |
| 2. Identifying the Largest Element of a Numpy Array.mp4 | 15.1 MB |
| 192 | 878.1 KB |
| 4. Decision Tree Algorithm with Python Part 3.mp4 | 14.7 MB |
| 193 | 296.7 KB |
| 2. Machine Learning Terminology.mp4 | 14.0 MB |
| 194 | 985.0 KB |
| 8. Combining Fancy Index with Normal Indexing.mp4 | 12.6 MB |
| 195 | 362.3 KB |
| 6. Creating NumPy Array with Eye() Function.mp4 | 12.6 MB |
| 196 | 436.6 KB |
| 2. Creating Pandas DataFrame with NumPy Array.mp4 | 12.1 MB |
| 197 | 918.6 KB |
| 5. Creating NumPy Array with Arange() Function.mp4 | 12.1 MB |
| 198 | 930.5 KB |
| 3. Creating Pandas Series with NumPy Array.mp4 | 12.0 MB |
| 199 | 36.8 KB |
| 10. Feature Scaling with the Robust Scaler Method for Machine Learning Algorithms.mp4 | 11.5 MB |
| 200 | 554.9 KB |
| 4. Creating NumPy Array with Full() Function.mp4 | 11.2 MB |
| 201 | 826.6 KB |
| 3. Detecting Least Element of Numpy Array Min(), Ar.mp4 | 10.2 MB |
| 202 | 830.4 KB |
| 2. Loading the Dataset.mp4 | 10.0 MB |
| 203 | 13.9 KB |
| 3. Principal Component Analysis (PCA) with Python Part 2.mp4 | 8.4 MB |
| 204 | 584.6 KB |
| 7. Creating NumPy Array with Linspace() Function.mp4 | 7.3 MB |
Name
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Size
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10.0 MB
[8
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2023-06-23
| Uploaded by FreeCourseWeb | Size 10.0 MB | Health [ 8 /1 ] | Added 2023-06-23 |
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2023-07-01
| Uploaded by FreeCourseWeb | Size 97.6 MB | Health [ 0 /0 ] | Added 2023-07-01 |
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37.1 MB
[12
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2023-07-01
| Uploaded by FreeCourseWeb | Size 37.1 MB | Health [ 12 /9 ] | Added 2023-07-01 |
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11.1 MB
[12
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2023-07-01
| Uploaded by FreeCourseWeb | Size 11.1 MB | Health [ 12 /4 ] | Added 2023-07-01 |
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13.2 MB
[9
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2023-07-01
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SOURCE: Machine Learning Data Science with Python Kaggle Pandas
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