Machine Learning Data Science with Python Kaggle |
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Name |
DOWNLOAD Copy Link | |
Total Size |
6.9 GB |
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Total Files |
289 |
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Last Seen |
2024-07-08 23:41 |
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Hash |
2A545E7471BAC02680D25E2AA085B5128C93F857 |
/.../20. Competition Section on Kaggle/ |
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201.0 MB |
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197.3 MB |
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/.../26. Introduction to Machine Learning with Real Hearth Attack Prediction Project/ |
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15.7 KB |
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4. Project Link File - Hearth Attack Prediction Project, Machine Learning.html |
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133.0 MB |
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122.8 MB |
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110.1 MB |
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80.2 MB |
/.../19. First Contact with Kaggle/ |
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11.2 KB |
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4. Project Link File - Hearth Attack Prediction Project, Machine Learning.html |
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135.9 MB |
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128.9 MB |
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45.7 MB |
/.../1. First Contact with Machine Learning/ |
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6.8 KB |
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6.4 KB |
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28.9 MB |
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14.7 MB |
/34. Extra/ |
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1. Machine Learning & Data Science with Python & Kaggle A-Z.html |
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/.../3. Evaluation Metrics in Machine Learning/ |
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2. Machine Learning Model Performance Evaluation Classification Error Metrics.mp4 |
105.2 MB |
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96.7 MB |
3. Evaluating Performance Regression Error Metrics in Python.mp4 |
47.9 MB |
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20.9 MB |
/.../4. Supervised Learning with Machine Learning/ |
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0.2 KB |
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33.2 MB |
/.../6. Bias Variance Trade-Off in Machine Learning/ |
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0.2 KB |
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57.7 MB |
/.../7. Logistic Regression Algorithm in Machine Learning A-Z/ |
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0.2 KB |
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85.4 MB |
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75.7 MB |
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49.4 MB |
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39.4 MB |
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36.5 MB |
1. What is Logistic Regression Algorithm in Machine Learning.mp4 |
29.2 MB |
/.../9. K Nearest Neighbors Algorithm in Machine Learning A-Z/ |
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0.2 KB |
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62.3 MB |
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36.7 MB |
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32.9 MB |
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30.0 MB |
/.../11. Decision Tree Algorithm in Machine Learning A-Z/ |
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0.2 KB |
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51.3 MB |
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44.5 MB |
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37.5 MB |
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34.2 MB |
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33.1 MB |
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15.4 MB |
/.../13. Support Vector Machine Algorithm in Machine Learning A-Z/ |
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0.2 KB |
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49.6 MB |
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43.7 MB |
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39.4 MB |
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37.3 MB |
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22.9 MB |
/.../14. Unsupervised Learning with Machine Learning/ |
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0.2 KB |
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17.7 MB |
/.../15. K Means Clustering Algorithm in Machine Learning A-Z/ |
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0.2 KB |
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31.4 MB |
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31.1 MB |
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30.4 MB |
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29.1 MB |
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18.0 MB |
/.../16. Hierarchical Clustering Algorithm in machine learning data science/ |
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0.2 KB |
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37.2 MB |
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30.3 MB |
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29.9 MB |
/.../18. Recommender System Algorithm in Machine Learning A-Z/ |
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0.2 KB |
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24.1 MB |
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18.8 MB |
/.../21. Dataset Section on Kaggle/ |
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0.2 KB |
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139.7 MB |
/.../22. Code Section on Kaggle/ |
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167.6 MB |
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110.9 MB |
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83.4 MB |
/.../23. Discussion Section on Kaggle/ |
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42.6 MB |
/.../24. Other Most Used Options on Kaggle/ |
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0.2 KB |
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112.2 MB |
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54.7 MB |
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42.9 MB |
/.../25. Details on Kaggle/ |
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85.5 MB |
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78.2 MB |
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61.3 MB |
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40.1 MB |
/.../27. First Organization/ |
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67.1 MB |
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66.6 MB |
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10.5 MB |
/.../28. Preparation For Exploratory Data Analysis (EDA)/ |
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48.0 MB |
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16.6 MB |
/.../29. Exploratory Data Analysis (EDA) - Uni-variate Analysis/ |
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4. Categoric Variables (Analysis with Pie Chart) Lesson 2.mp4 |
88.2 MB |
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84.2 MB |
3. Categoric Variables (Analysis with Pie Chart) Lesson 1.mp4 |
78.4 MB |
5. Examining the Missing Data According to the Analysis Result.mp4 |
56.4 MB |
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20.7 MB |
/.../30. Exploratory Data Analysis (EDA) - Bi-variate Analysis/ |
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0.2 KB |
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95.8 MB |
16. Relationships between variables (Analysis with Heatmap) Lesson 2.mp4 |
95.1 MB |
12. Numerical - Categorical Variables (Analysis with Swarm Plot) Lesson 2.mp4 |
71.4 MB |
4. Categoric Variables – Target Variable (Analysis with Count Plot) Lesson 2.mp4 |
59.0 MB |
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55.4 MB |
1. Numeric Variables – Target Variable (Analysis with FacetGrid) Lesson 1.mp4 |
51.8 MB |
7. Examining Numeric Variables Among Themselves (Analysis with Pair Plot) Lesson 2.mp4 |
49.4 MB |
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46.7 MB |
11. Numerical - Categorical Variables (Analysis with Swarm Plot) Lesson 1.mp4 |
43.7 MB |
13. Numerical - Categorical Variables (Analysis with Box Plot) Lesson 1.mp4 |
39.9 MB |
15. Relationships between variables (Analysis with Heatmap) Lesson 1.mp4 |
38.1 MB |
2. Numeric Variables – Target Variable (Analysis with FacetGrid) Lesson 2.mp4 |
37.4 MB |
14. Numerical - Categorical Variables (Analysis with Box Plot) Lesson 2.mp4 |
37.2 MB |
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36.9 MB |
5. Examining Numeric Variables Among Themselves (Analysis with Pair Plot) Lesson 1.mp4 |
29.7 MB |
3. Categoric Variables – Target Variable (Analysis with Count Plot) Lesson 1.mp4 |
25.3 MB |
/.../31. Preparation for Modelling in Machine Learning/ |
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46.1 MB |
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44.9 MB |
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38.0 MB |
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37.8 MB |
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36.6 MB |
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31.2 MB |
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28.1 MB |
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26.4 MB |
9. Applying One Hot Encoding Method to Categorical Variables.mp4 |
25.3 MB |
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25.2 MB |
10. Feature Scaling with the Robust Scaler Method for Machine Learning Algorithms.mp4 |
12.0 MB |
/.../32. Modelling for machine learning/ |
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0.2 KB |
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61.6 MB |
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55.2 MB |
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43.7 MB |
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31.7 MB |
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31.2 MB |
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30.8 MB |
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26.9 MB |
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25.7 MB |
/33. Conclusion/ |
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30.0 MB |
/.pad/ |
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239.2 KB |
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831.5 KB |
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137.4 KB |
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856.7 KB |
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392.6 KB |
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133.1 KB |
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92.8 KB |
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697.4 KB |
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996.3 KB |
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223.1 KB |
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956.8 KB |
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488.4 KB |
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577.9 KB |
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718.1 KB |
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536.6 KB |
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862.3 KB |
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255.4 KB |
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406.5 KB |
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796.9 KB |
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760.0 KB |
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833.4 KB |
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/.../2. Installations for Python/ |
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124.1 MB |
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120.4 MB |
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48.6 MB |
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28.7 MB |
/.../5. Linear Regression Algorithm in Machine Learning A-Z/ |
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112.1 MB |
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94.4 MB |
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79.9 MB |
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73.7 MB |
1. Linear Regression Algorithm Theory in Machine Learning A-Z.mp4 |
35.7 MB |
/.../10. Hyperparameter Optimization/ |
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49.8 MB |
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34.7 MB |
/.../12. Random Forest Algorithm in Machine Learning A-Z/ |
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40.6 MB |
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40.5 MB |
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24.0 MB |
/.../17. Principal Component Analysis (PCA) in Machine Learning A-Z/ |
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39.8 MB |
4. Principal Component Analysis (PCA) with Python Part 3.mp4 |
39.1 MB |
2. Principal Component Analysis (PCA) with Python Part 1.mp4 |
27.3 MB |
3. Principal Component Analysis (PCA) with Python Part 2.mp4 |
8.8 MB |
/.../8. K-fold Cross-Validation in Machine Learning A-Z/ |
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36.4 MB |
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18.3 MB |
Total files 289 |
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