- PyTorch Tutorial
- PyTorch - Home
- PyTorch - Introduction
- PyTorch - Installation
- Mathematical Building Blocks of Neural Networks
- PyTorch - Neural Network Basics
- Universal Workflow of Machine Learning
- Machine Learning vs. Deep Learning
- Implementing First Neural Network
- 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
- Training a Convent from Scratch
- PyTorch - Feature Extraction in Convents
- PyTorch - Visualization of Convents
- Sequence Processing with Convents
- PyTorch - Word Embedding
- PyTorch - Recursive Neural Networks
- PyTorch Useful Resources
- PyTorch - Quick Guide
- PyTorch - Useful Resources
- PyTorch - Discussion
PyTorch Tutorial
PyTorch is an open source machine learning library for Python and is completely based on Torch. It is primarily used for applications such as natural language processing. PyTorch is developed by Facebook's artificial-intelligence research group along with Uber's "Pyro" software for the concept of in-built probabilistic programming.
Audience
This tutorial has been prepared for python developers who focus on research and development with machinelearning algorithms along with natural language processing system. The aim of this tutorial is to completely describe all concepts of PyTorch and realworld examples of the same.
Prerequisites
Before proceeding with this tutorial, you need knowledge of Python and Anaconda framework (commands used in Anaconda). Having knowledge of artificial intelligence concepts will be an added advantage.