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

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