PyTorch for Deep Learning & Machine Learning – Full Course

Learn PyTorch for deep learning in this comprehensive course for beginners. PyTorch is a machine learning framework written in Python. Some sections below have been left out because of the YouTube limit for timestamps. 0:00:00 Introduction ? Chapter 0 – PyTorch Fundamentals 0:01:45 0. Welcome and "what is deep learning?" 0:07:41 1. Why use machine/deep learning? 0:11:15 2. The number one rule of ML 0:16:55 3. Machine learning vs deep learning 0:23:02 4. Anatomy of neural networks 0:32:24 5. Different learning paradigms 0:36:56 6. What can deep learning be used for? 0:43:18 7. What is/why PyTorch? 0:53:33 8. What are tensors? 0:57:52 9. Outline 1:03:56 10. How to (and how not to) approach this course 1:09:05 11. Important resources 1:14:28 12. Getting setup 1:22:08 13. Introduction to tensors 1:35:35 14. Creating tensors 1:54:01 17. Tensor datatypes 2:03:26 18. Tensor attributes (information about tensors) 2:11:50 19. Manipulating tensors 2:17:50 20. Matrix multiplication 2:48:18 23. Finding the min, max, mean & sum 2:57:48 25. Reshaping, viewing and stacking 3:11:31 26. Squeezing, unsqueezing and permuting 3:23:28 27. Selecting data (indexing) 3:33:01 28. PyTorch and NumPy 3:42:10 29. Reproducibility 3:52:58 30. Accessing a GPU 4:04:49 31. Setting up device agnostic code ? Chapter 1 – PyTorch Workflow 4:17:27 33. Introduction to PyTorch Workflow 4:20:14 34. Getting setup 4:27:30 35. Creating a dataset with linear regression 4:37:12 36. Creating training and test sets...