The StatQuest Introduction to PyTorch

PyTorch is one of the most popular tools for making Neural Networks. This StatQuest walks you through a simple example of how to use PyTorch one step at a time. By the end of this StatQuest, you'll know how to create a new neural network from scratch, make predictions and graph the output, and optimize a parameter using backpropagation. BAM!!! To learn more about Lightning: https://lightning.ai/ The code demonstrated this video can be downloaded here: https://lightning.ai/lightning-ai/stu... This StatQuest assumes that you are already familiar with... Neural Networks:    • The Essential Main Ideas of Neural Networks   Backpropagation:    • Neural Networks Pt. 2: Backpropagation Mai...   The ReLU Activation Function:    • Neural Networks Pt. 3: ReLU In Action!!!   Tensors:    • Tensors for Neural Networks, Clearly Expla...   To install PyTorch see: https://pytorch.org/get-started/locally/ To install matplotlib, see: https://matplotlib.org/stable/users/g... To install seaborn, see: https://seaborn.pydata.org/installing... For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ If you'd like to support StatQuest, please consider... Patreon:   / statquest   ...or... YouTube Membership:    / @statquest   ...buying one of my books, a study guide, a t-shirt or hoodie, or a song from the StatQuest store... https://statquest.org/statquest-store/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter:   / joshuastarmer   0:00 Awesome song and introduction 1:38 Coding preliminaries 2:15 Creating a neural network in PyTorch 7:54 Graphing the neural network's output 10:47 Optimizing a parameter with backpropagation #StatQuest #NeuralNetworks #PyTorch