PyTorch Tutorials - Complete Beginner Course - PyTorch Tutorial 13 - Feed-Forward Neural Network

New Tutorial series about Deep Learning with PyTorch! ⭐ 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 * In this part we will implement our first multilayer neural network that can do digit classification based on the famous MNIST dataset. We put all the things from the last tutorials together: - Use the DataLoader to load our dataset and apply a transform to the dataset - Implement a feed-forward neural net with input layer, hidden layer, and output layer - Apply activation functions. - Set up loss and optimizer - Training loop that can use batch training. - Evaluate our model and calculate the accuracy. - Additionally, we will make sure that our whole code can also run on the gpu if we have gpu support. 📚 Get my FREE NumPy Handbook: https://www.python-engineer.com/numpybook 📓 Notebooks available on Patreon: https://www.patreon.com/patrickloeber ⭐ Join Our Discord : https://discord.gg/FHMg9tKFSN Part 13: Feed-Forward Neural Network If you enjoyed this video, please subscribe to the channel! Official website: https://pytorch.org/ Part 01: https://youtu.be/EMXfZB8FVUA Code for this tutorial series: https://github.com/patrickloeber/pytorchTutorial You can find me here: Website: https://www.python-engineer.com Twitter: https://twitter.com/patloeber GitHub: https://github.com/patrickloeber #Python #DeepLearning #Pytorch ---------------------------------------------------------------------------------------------------------- * 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! 🙏