PyTorch Tutorials - Complete Beginner Course
Embark on a comprehensive journey through PyTorch with this 7-hour tutorial series. Begin with installation and tensor basics, then progress to advanced concepts like gradient calculation, backpropagation, and autograd. Master essential components of the training pipeline including models, loss functions, and optimizers. Dive into practical applications with linear and logistic regression, dataset handling, and batch training. Explore crucial deep learning topics such as activation functions, feed-forward neural networks, and convolutional neural networks (CNNs). Advance your skills with transfer learning, TensorBoard usage, and model saving/loading techniques. Gain hands-on experience by creating and deploying a deep learning app using Flask and Heroku. Delve into recurrent neural networks (RNNs) with tutorials on LSTM and GRU. Discover PyTorch Lightning for streamlined research workflows and learn to optimize your models with learning rate schedulers.