Udemy - Deep Learning Prerequisites: Linear Regression in Python

Files:

• 1. Welcome.mp4 (49.7 MB)
• 1. Welcome.vtt (4.0 KB)
• 2. Introduction and Outline.mp4 (6.3 MB)
• 2. Introduction and Outline.vtt (5.3 KB)
• 3. What is machine learning How does linear regression play a role.mp4 (8.4 MB)
• 3. What is machine learning How does linear regression play a role.vtt (5.3 KB)
• 4. Introduction to Moore's Law Problem.mp4 (4.4 MB)
• 4. Introduction to Moore's Law Problem.vtt (3.4 KB)
• 5. What can linear regression be used for.html (0.1 KB)
• 6. How to Succeed in this Course.mp4 (3.3 MB)
• 6. How to Succeed in this Course.vtt (3.5 KB)

• 1. Define the model in 1-D, derive the solution (Updated Version).mp4 (19.3 MB)
• 1. Define the model in 1-D, derive the solution (Updated Version).vtt (14.4 KB)
• 2. Define the model in 1-D, derive the solution.mp4 (24.7 MB)
• 2. Define the model in 1-D, derive the solution.vtt (9.6 KB)
• 3. Coding the 1-D solution in Python.mp4 (14.4 MB)
• 3. Coding the 1-D solution in Python.vtt (4.9 KB)
• 4. Exercise Theory vs. Code.mp4 (1.0 MB)
• 4. Exercise Theory vs. Code.vtt (1.4 KB)
• 5. Determine how good the model is - r-squared.mp4 (11.3 MB)
• 5. Determine how good the model is - r-squared.vtt (4.1 KB)
• 6. R-squared in code.mp4 (4.5 MB)
• 6. R-squared in code.vtt (1.5 KB)
• 7. Demonstrating Moore's Law in Code.mp4 (17.5 MB)
• 7. Demonstrating Moore's Law in Code.vtt (6.2 KB)
• 8. R-squared Quiz 1.mp4 (2.8 MB)
• 8. R-squared Quiz 1.vtt (2.0 KB)

• 1. Define the multi-dimensional problem and derive the solution (Updated Version).mp4 (14.4 MB)
• 1. Define the multi-dimensional problem and derive the solution (Updated Version).vtt (10.3 KB)
• 2. Define the multi-dimensional problem and derive the solution.mp4 (36.1 MB)
• 2. Define the multi-dimensional problem and derive the solution.vtt (11.4 KB)
• 3. How to solve multiple linear regression using only matrices.mp4 (3.1 MB)
• 3. How to solve multiple linear regression using only matrices.vtt (1.8 KB)
• 4. Coding the multi-dimensional solution in Python.mp4 (14.9 MB)
• 4. Coding the multi-dimensional solution in Python.vtt (4.5 KB)
• 5. Polynomial regression - extending linear regression (with Python code).mp4 (16.4 MB)
• 5. Polynomial regression - extending linear regression (with Python code).vtt (4.3 KB)
• 6. Predicting Systolic Blood Pressure from Age and Weight.mp4 (12.3 MB)
• 6. Predicting Systolic Blood Pressure from Age and Weight.vtt (4.9 KB)
• 7. R-squared Quiz 2.mp4 (3.5 MB)
• 7. R-squared Quiz 2.vtt (2.4 KB)

• 1. What do all these letters mean.mp4 (9.6 MB)
• 1. What do all these letters mean.vtt (7.0 KB)
• 10. The Dummy Variable Trap.mp4 (6.1 MB)
• 10. The Dummy Variable Trap.vtt (4.9 KB)
• 11. Gradient Descent Tutorial.mp4 (22.8 MB)
• 11. Gradient Descent Tutorial.vtt (4.8 KB)
• 12. Gradient Descent for Linear Regression.mp4 (3.5 MB)
• 12. Gradient Descent for Linear Regression.vtt (2.8 KB)
• 13. Bypass the Dummy Variable Trap with Gradient Descent.mp4 (8.5 MB)
• 13. Bypass the Dummy Variable Trap with Gradient Descent.vtt (3.1 KB)
• 14. L1 Regularization - Theory.mp4 (4.7 MB)
• 14. L1 Regularization - Theory.vtt (3.6 KB)
• 15. L1 Regularization - Code.mp4 (8.3 MB)
• 15. L1 Regularization - Code.vtt (3.1 KB)
• 16. L1 vs L2 Regularization.mp4 (4.8 MB)
• 16. L1 vs L2 Regularization.vtt (3.7 KB)
• 2. Interpreting the Weights.mp4 (6.1 MB)
• 2. Interpreting the Weights.vtt (3.7 KB)
• 3. Generalization error, train and test sets.mp4 (4.4 MB)
• 3. Generalization error, train and test sets.vtt (2.6 KB)
• 4. Generalization and Overfitting Demonstration in Code.mp4 (17.3 MB)
• 4. Generalization and Overfitting Demonstration in Code.vtt (8.2 KB)
• 5. Categorical inputs.mp4 (8.2 MB)
• 5. Categorical inputs.vtt (4.3 KB)
• 6. One-Hot Encoding Quiz.mp4 (3.8 MB)
• 6. One-Hot Encoding Quiz.vtt (2.2 KB)
• 7. Probabilistic Interpretation of Squared Error.mp4 (8.1 MB)
• 7. Probabilistic Interpretation of Squared Error.vtt (5.7 KB)
• 8. L2 Regularization - Theory.mp4 (6.7 MB)
• 8. L2 Regularization - Theory.vtt (4.8 KB)
• 9. L2 Regularization - Code.mp4 (8.1 MB)
• 9. L2 Regularization - Code.vtt (3.0 KB)

• 1. Brief overview of advanced linear regression and machine learning topics.mp4 (8.1 MB)
• 1. Brief overview of advanced linear regression and machine learning topics.vtt (5.1 KB)
• 2. Exercises, practice, and how to get good at this.mp4 (7.2 MB)
• 2. Exercises, practice, and how to get good at this.vtt (4.8 KB)

• 1. What is the Appendix.mp4 (5.5 MB)
• 1. What is the Appendix.vtt (3.3 KB)
• 10. What order should I take your courses in (part 1).mp4 (29.3 MB)
• 10. What order should I take your courses in (part 1).vtt (14.1 KB)
• 11. What order should I take your courses in (part 2).mp4 (37.6 MB)
• 11. What order should I take your courses in (part 2).vtt (37.6 MB)
• 12. Python 2 vs Python 3.mp4 (7.8 MB)
• 12. Python 2 vs Python 3.vtt (5.4 KB)
• 2. BONUS Where to get Udemy coupons and FREE deep learning material.mp4 (4.0 MB)
• 2. BONUS Where to get Udemy coupons and FREE deep learning material.vtt (3.0 KB)
• 3. Windows-Focused Environment Setup 2018.mp4 (186.3 MB)
• 3. Windows-Focused Environment Setup 2018.vtt (17.4 KB)
• 4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 (43.9 MB)
• 4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.vtt (12.4 KB)
• 5. How to Code by Yourself (part 1).mp4 (24.5 MB)
• 5. How to Code by Yourself (part 1).vtt (19.8 KB)
• 6. How to Code