PyTorch is defined as an open source machine learning library for Python. It is used for applications such as natural language processing.

PyTorch redesigns and implements Torch in Python while sharing the same core C libraries for the backend code.

PyTorch developers tuned this back-end code to run Python efficiently.

They also kept the GPU based hardware acceleration as well as the extensibility features that made Lua-based Torch.

List of topics covered in this tutorial :

PyTorch - Introduction
PyTorch - Installation
Mathematical Building Blocks of Neural Networks
PyTorch - Neural Network Basics
Universal Workflow of Machine Learning
PyTorch - Machine Learning vs. Deep Learning
PyTorch - Implementing First Neural Network
PyTorch - Neural Networks to Functional Blocks
PyTorch - Terminologies
PyTorch - Loading Data
PyTorch - Linear Regression
PyTorch - Convolutional Neural Network
PyTorch - Recurrent Neural Network
PyTorch - Datasets
PyTorch - Introduction to Convents
PyTorch - Training a Convent from Scratch
PyTorch - Feature Extraction in Convents
PyTorch - Visualization of Convents
PyTorch - Sequence Processing with Convents
PyTorch - Word Embedding
PyTorch - Recursive Neural Networks