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34. Any Feedback on this Section.html 512
33. Download the Complete Notebook Here.html 242
33.3 boston_valuation.py 3.1K
33.2 04 Valuation Tool.ipynb.zip 2.9K
33.1 04 Multivariable Regression.ipynb.zip 3.5M
32. Build a Valuation Tool (Part 3) Docstrings & Creating your own Python Module.srt 28K
32. Build a Valuation Tool (Part 3) Docstrings & Creating your own Python Module.mp4 244M
31. Python Conditional Statement Coding Exercise.html 156
30. [Python] - Conditional Statements - Build a Valuation Tool (Part 2).srt 21K
30. [Python] - Conditional Statements - Build a Valuation Tool (Part 2).mp4 134M
29. Build a Valuation Tool (Part 1) Working with Pandas Series & Numpy ndarrays.srt 21K
29. Build a Valuation Tool (Part 1) Working with Pandas Series & Numpy ndarrays.mp4 131M
28. Making Predictions (Part 2) Standard Deviation, RMSE, and Prediction Intervals.srt 15K
28. Making Predictions (Part 2) Standard Deviation, RMSE, and Prediction Intervals.mp4 85M
27. Making Predictions (Part 1) MSE & R-Squared.srt 24K
27. Making Predictions (Part 1) MSE & R-Squared.mp4 153M
26. Residual Analysis (Part 2) Graphing and Comparing Regression Residuals.srt 23K
26. Residual Analysis (Part 2) Graphing and Comparing Regression Residuals.mp4 153M
25. Residual Analysis (Part 1) Predicted vs Actual Values.srt 18K
25. Residual Analysis (Part 1) Predicted vs Actual Values.mp4 124M
24. How to Analyse and Plot Regression Residuals.srt 15K
24. How to Analyse and Plot Regression Residuals.mp4 64M
23. Model Simplification & Baysian Information Criterion.srt 23K
23. Model Simplification & Baysian Information Criterion.mp4 150M
22. Understanding VIF & Testing for Multicollinearity.srt 26K
22. Understanding VIF & Testing for Multicollinearity.mp4 144M
21. How to Interpret Coefficients using p-Values and Statistical Significance.srt 11K
21. How to Interpret Coefficients using p-Values and Statistical Significance.mp4 65M
20. Improving the Model by Transforming the Data.srt 22K
20. Improving the Model by Transforming the Data.mp4 127M
19. Introduction to Model Evaluation.srt 3.8K
19. Introduction to Model Evaluation.mp4 16M
18. How to Calculate the Model Fit with R-Squared.srt 4.4K
18. How to Calculate the Model Fit with R-Squared.mp4 32M
17. Running a Multivariable Regression.srt 9.8K
17. Running a Multivariable Regression.mp4 56M
16. How to Shuffle and Split Training & Testing Data.srt 12K
16. How to Shuffle and Split Training & Testing Data.mp4 64M
15. Understanding Multivariable Regression.srt 7.5K
15. Understanding Multivariable Regression.mp4 49M
14. Working with Seaborn Pairplots & Jupyter Microbenchmarking Techniques.srt 29K
14. Working with Seaborn Pairplots & Jupyter Microbenchmarking Techniques.mp4 214M
13. A Note for the Next Lesson.html 476
12. Techniques to Style Scatter Plots.srt 21K
12. Techniques to Style Scatter Plots.mp4 129M
11. Visualising Correlations with a Heatmap.srt 24K
11. Visualising Correlations with a Heatmap.mp4 169M
10. Calculating Correlations and the Problem posed by Multicollinearity.srt 18K
10. Calculating Correlations and the Problem posed by Multicollinearity.mp4 111M
9. Introduction to Correlation Understanding Strength & Direction.srt 8.4K
9. Introduction to Correlation Understanding Strength & Direction.mp4 33M
8. Understanding Descriptive Statistics the Mean vs the Median.srt 12K
8. Understanding Descriptive Statistics the Mean vs the Median.mp4 62M
7. Working with Index Data, Pandas Series, and Dummy Variables.srt 21K
7. Working with Index Data, Pandas Series, and Dummy Variables.mp4 141M
6. Visualising Data (Part 2) Seaborn and Probability Density Functions.srt 9.0K
6. Visualising Data (Part 2) Seaborn and Probability Density Functions.mp4 57M
5. Visualising Data (Part 1) Historams, Distributions & Outliers.srt 14K
5. Visualising Data (Part 1) Historams, Distributions & Outliers.mp4 65M
4. Clean and Explore the Data (Part 2) Find Missing Values.srt 19K
4. Clean and Explore the Data (Part 2) Find Missing Values.mp4 135M
3. Clean and Explore the Data (Part 1) Understand the Nature of the Dataset.srt 16K
3. Clean and Explore the Data (Part 1) Understand the Nature of the Dataset.mp4 87M
2. Gathering the Boston House Price Data.srt 8.7K
2. Gathering the Boston House Price Data.mp4 56M
1. Defining the Problem.srt 6.5K
1. Defining the Problem.mp4 40M
1.1 Course Resources.html 122