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8. [Python] - Advanced Functions and the Pitfalls of Optimisation (Part 1).mp4 291M
6. [Python] - Loops and the Gradient Descent Algorithm.mp4 287M
10. Understanding the Learning Rate.mp4 237M
9. [Python] - Tuples and the Pitfalls of Optimisation (Part 2).mp4 219M
11. How to Create 3-Dimensional Charts.mp4 193M
15. Reshaping and Slicing N-Dimensional Arrays.mp4 141M
12. Understanding Partial Derivatives and How to use SymPy.mp4 133M
14. [Python] - Loops and Performance Considerations.mp4 131M
21. Plotting the Mean Squared Error (MSE) on a Surface (Part 2).mp4 125M
22. Running Gradient Descent with a MSE Cost Function.mp4 111M
4. LaTeX Markdown and Generating Data with Numpy.mp4 91M
5. Understanding the Power Rule & Creating Charts with Subplots.mp4 90M
18. Transposing and Reshaping Arrays.mp4 87M
13. Implementing Batch Gradient Descent with SymPy.mp4 87M
19. Implementing a MSE Cost Function.mp4 81M
23. Visualising the Optimisation on a 3D Surface.mp4 75M
20. Understanding Nested Loops and Plotting the MSE Function (Part 1).mp4 73M
16. Concatenating Numpy Arrays.mp4 71M
3. Introduction to Cost Functions.mp4 66M
17. Introduction to the Mean Squared Error (MSE).mp4 65M
2. How a Machine Learns.mp4 23M
1. What's Coming Up.mp4 21M
24.1 03 Gradient Descent.ipynb.zip 1.1M
6. [Python] - Loops and the Gradient Descent Algorithm.srt 44K
8. [Python] - Advanced Functions and the Pitfalls of Optimisation (Part 1).srt 43K
10. Understanding the Learning Rate.srt 38K
9. [Python] - Tuples and the Pitfalls of Optimisation (Part 2).srt 34K
11. How to Create 3-Dimensional Charts.srt 26K
15. Reshaping and Slicing N-Dimensional Arrays.srt 23K
22. Running Gradient Descent with a MSE Cost Function.srt 22K
12. Understanding Partial Derivatives and How to use SymPy.srt 20K
5. Understanding the Power Rule & Creating Charts with Subplots.srt 18K
14. [Python] - Loops and Performance Considerations.srt 18K
21. Plotting the Mean Squared Error (MSE) on a Surface (Part 2).srt 17K
4. LaTeX Markdown and Generating Data with Numpy.srt 17K
20. Understanding Nested Loops and Plotting the MSE Function (Part 1).srt 14K
19. Implementing a MSE Cost Function.srt 14K
18. Transposing and Reshaping Arrays.srt 14K
13. Implementing Batch Gradient Descent with SymPy.srt 13K
17. Introduction to the Mean Squared Error (MSE).srt 13K
23. Visualising the Optimisation on a 3D Surface.srt 11K
3. Introduction to Cost Functions.srt 9.5K
16. Concatenating Numpy Arrays.srt 8.9K
2. How a Machine Learns.srt 7.2K
1. What's Coming Up.srt 3.8K
25. Any Feedback on this Section.html 520
24. Download the Complete Notebook Here.html 242
7. Python Loops Coding Exercise.html 156
1.1 Course Resources.html 122