PDC4S:\IT\DATA SCIENCE AND MACHINE LEARNING\Data Science A-Z Real-Life Data Science Excercises Included\10. Multiple Linear Regression

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1. Intro (what you will learn in this section).mp447,210 KB12/12/2021 3:34 AM
1. Intro (what you will learn in this section).srt3 KB12/12/2021 3:34 AM
10. Interpreting coefficients of MLR.mp4172,727 KB12/12/2021 3:34 AM
10. Interpreting coefficients of MLR.srt19 KB12/12/2021 3:34 AM
11. Section Recap.mp430,608 KB12/12/2021 3:34 AM
11. Section Recap.srt7 KB12/12/2021 3:34 AM
2. Caveat assumptions of a linear regression.mp48,274 KB12/12/2021 3:34 AM
2. Caveat assumptions of a linear regression.srt3 KB12/12/2021 3:34 AM
3. Get the dataset.mp463,790 KB12/12/2021 3:34 AM
3. Get the dataset.srt7 KB12/12/2021 3:34 AM
4. Dummy Variables.mp471,435 KB12/12/2021 3:34 AM
4. Dummy Variables.srt13 KB12/12/2021 3:34 AM
5. Dummy Variable Trap.mp421,389 KB12/12/2021 3:34 AM
5. Dummy Variable Trap.srt4 KB12/12/2021 3:34 AM
6. Understanding the P-Value.mp457,848 KB12/12/2021 3:34 AM
6. Understanding the P-Value.srt21 KB12/12/2021 3:34 AM
7. Ways to build a model BACKWARD, FORWARD, STEPWISE.mp4101,231 KB12/12/2021 3:34 AM
7. Ways to build a model BACKWARD, FORWARD, STEPWISE.srt24 KB12/12/2021 3:34 AM
8. Backward Elimination - Practice time.mp4191,413 KB12/12/2021 3:34 AM
8. Backward Elimination - Practice time.srt26 KB12/12/2021 3:34 AM
9. Using Adjusted R-squared to create Robust models.mp4171,176 KB12/12/2021 3:34 AM
9. Using Adjusted R-squared to create Robust models.srt16 KB12/12/2021 3:34 AM