Deep Learning With PyTorch - Full Course

Deep Learning With PyTorch - Full Course

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Deep Learning With PyTorch - Full Course
In this course you learn all the fundamentals to get started with PyTorch and Deep Learning. ⭐ Check out Tabnine, the FREE AI-powered code completion tool I use to help me code faster: https://www.tabnine.com/?utm_source=youtube.com&utm_campaign=PythonEngineer * Find Python and ML jobs: https://pythonengineer.pallet.com Get my Free NumPy Handbook: https://www.python-engineer.com/numpybook If you enjoyed this video, please subscribe to the channel: https://www.youtube.com/channel/UCbXgNpp0jedKWcQiULLbDTA?sub_confirmation=1 Code: https://github.com/patrickloeber/pytorchTutorial Playlist with single videos: https://www.youtube.com/watch?v=EMXfZB8FVUA&list=PLqnslRFeH2UrcDBWF5mfPGpqQDSta6VK4 Dataset for Transfer Learning tutorial: https://download.pytorch.org/tutorial/hymenoptera_data.zip ~~~~~~~~~~~~~~~ CONNECT ~~~~~~~~~~~~~~~ 🖥️ Website: https://www.python-engineer.com 🐦 Twitter - https://twitter.com/patloeber 📸 Instagram - https://www.instagram.com/patloeber 🦾 Discord: https://discord.gg/FHMg9tKFSN 💻 GitHub: https://github.com/patrickloeber ~~~~~~~~~~~~~~ SUPPORT ME ~~~~~~~~~~~~~~ 🅿 Patreon - https://www.patreon.com/patrickloeber #Python #PyTorch Timeline: 00:00 - Intro 01:42 - 1 Installation 07:30 - 2 Tensor Basics 26:02 - 3 Autograd 42:00 - 4 Backpropagation 55:18 - 5 Gradient Descent 1:12:53 - 6 Training Pipeline 1:27:14 - 7 Linear Regression 1:39:30 - 8 Logistic Regression 1:57:56 - 9 Dataset and Dataloader 2:13:28 - 10 Dataset Transforms 2:24:14 - 11 Softmax and Crossentropy 2:42:36 - 12 Activation Functions 2:52:40 - 13 Feed Forward Net 3:14:18 - 14 CNN 3:36:30 - 15 Transfer Learning 3:51:30 - 16 Tensorboard 4:17:14 - 17 Save & Load Models ---------------------------------------------------------------------------------------------------------- * This is a sponsored link. By clicking on it you will not have any additional costs, instead you will support me and my project. Thank you so much for the support! 🙏