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| Archived
files |
|
01 - Course Overview\01 - Course Overview.mp4
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|
3,805,516 |
FEA69894 |
|
02 - Understanding Linear Regression as a Machine Learning Problem\02 - Module Overview.mp4
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1,879,492 |
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|
02 - Understanding Linear Regression as a Machine Learning Problem\03 - Prerequisites and Course Outline.mp4
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2,072,318 |
E0FD2F70 |
|
02 - Understanding Linear Regression as a Machine Learning Problem\04 - Module Summary.mp4
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1,688,172 |
C56B8380 |
|
02 - Understanding Linear Regression as a Machine Learning Problem\05 - Connecting the Dots with Linear Regression.mp4
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|
10,582,745 |
E6B7D4E0 |
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02 - Understanding Linear Regression as a Machine Learning Problem\06 - Minimizing Least Square Error.mp4
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|
6,519,951 |
421FB637 |
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02 - Understanding Linear Regression as a Machine Learning Problem\07 - Installing and Setting up scikit-learn.mp4
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4,862,968 |
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|
02 - Understanding Linear Regression as a Machine Learning Problem\08 - Exploring the Automobile Mpg Dataset.mp4
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15,213,091 |
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02 - Understanding Linear Regression as a Machine Learning Problem\09 - Visualizing Relationships and Correlations in Features.mp4
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|
11,738,530 |
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02 - Understanding Linear Regression as a Machine Learning Problem\10 - Mitigating Risks in Simple and Multiple Regression.mp4
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9,127,735 |
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02 - Understanding Linear Regression as a Machine Learning Problem\11 - R-squared and Adjusted R-squared.mp4
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2,318,839 |
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02 - Understanding Linear Regression as a Machine Learning Problem\12 - Regression with Categorical Variables.mp4
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5,986,280 |
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|
03 - Building a Simple Linear Model\13 - Module Overview.mp4
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03 - Building a Simple Linear Model\14 - Simple Linear Regression .mp4
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03 - Building a Simple Linear Model\15 - Linear Regression with Multiple Features.mp4
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03 - Building a Simple Linear Model\16 - Standardizing Numeric Data.mp4
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03 - Building a Simple Linear Model\17 - Label Encoding and One-hot Encoding Categorical Data.mp4
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03 - Building a Simple Linear Model\18 - Linear Regression and the Dummy Trap.mp4
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12,722,768 |
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03 - Building a Simple Linear Model\19 - Module Summary.mp4
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04 - Building Regularized Regression Models\20 - Module Overview.mp4
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|
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04 - Building Regularized Regression Models\21 - Overview of Regression Models in scikit-learn.mp4
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3,501,307 |
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04 - Building Regularized Regression Models\22 - Overfitting and Regularization.mp4
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04 - Building Regularized Regression Models\23 - Lasso, Ridge and Elastic Net Regression.mp4
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|
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04 - Building Regularized Regression Models\24 - Defining Helper Functions to Build and Train Models and Compare Results.mp4
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04 - Building Regularized Regression Models\25 - Single Feature, Kitchen Sink, and Parsimonious Linear Regression.mp4
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04 - Building Regularized Regression Models\26 - Lasso Regression.mp4
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6,744,210 |
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04 - Building Regularized Regression Models\27 - Ridge Regression.mp4
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4,313,476 |
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04 - Building Regularized Regression Models\28 - Elastic Net Regression.mp4
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|
04 - Building Regularized Regression Models\29 - Module Summary.mp4
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1,907,071 |
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05 - Performing Regression Using Multiple Techniques\30 - Module Overview.mp4
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|
2,057,470 |
702F3EE4 |
|
05 - Performing Regression Using Multiple Techniques\31 - Choosing Regression Algorithms.mp4
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4,353,651 |
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|
05 - Performing Regression Using Multiple Techniques\32 - Least Angle Regression.mp4
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|
5,485,130 |
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|
05 - Performing Regression Using Multiple Techniques\33 - Implementing Least Angle Regression.mp4
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|
2,503,734 |
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05 - Performing Regression Using Multiple Techniques\34 - Regression with Polynomial Relationships.mp4
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2,625,989 |
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|
05 - Performing Regression Using Multiple Techniques\35 - Module Summary.mp4
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|
2,178,786 |
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|
05 - Performing Regression Using Multiple Techniques\36 - Support Vector Regression.mp4
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|
9,055,245 |
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05 - Performing Regression Using Multiple Techniques\37 - Implementing Support Vector Regression.mp4
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|
6,357,293 |
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05 - Performing Regression Using Multiple Techniques\38 - Nearest Neighbors Regression.mp4
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05 - Performing Regression Using Multiple Techniques\39 - Implementing K-nearest-neighbors Regression.mp4
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4,637,187 |
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05 - Performing Regression Using Multiple Techniques\40 - Stochastic Gradient Descent Regression.mp4
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|
4,526,013 |
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05 - Performing Regression Using Multiple Techniques\41 - Implementing Stochastic Gradient Descent Regression.mp4
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4,727,856 |
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|
05 - Performing Regression Using Multiple Techniques\42 - Decision Tree Regression.mp4
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|
6,660,477 |
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05 - Performing Regression Using Multiple Techniques\43 - Implementing Decision Tree Regression.mp4
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3,252,737 |
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|
06 - Hyperparameter Tuning for Regression Models\44 - Module Overview.mp4
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1,560,454 |
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06 - Hyperparameter Tuning for Regression Models\45 - Hyperparameter Tuning.mp4
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06 - Hyperparameter Tuning for Regression Models\46 - Hyperparameter Tuning for Lasso Regression Using Grid Search.mp4
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06 - Hyperparameter Tuning for Regression Models\47 - Tuning Different Regression Models Using Grid Search.mp4
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06 - Hyperparameter Tuning for Regression Models\48 - Summary and Further Study.mp4
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building-regression-models-scikit-learn.zip |
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01 - Course Overview |
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02 - Understanding Linear Regression as a Machine Learning Problem |
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03 - Building a Simple Linear Model |
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04 - Building Regularized Regression Models |
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05 - Performing Regression Using Multiple Techniques |
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06 - Hyperparameter Tuning for Regression Models |
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| Total size: |
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