In this Pytorch tutorial, you will be given an introduction to Pytorch. This Pytorch tutorial will teach you about Tensor- one of the most basic objects in Pytorch. Along with that, the tutorial also covers various functions that will be used to train neural networks and process data. Some concepts about broadcasting, reshaping, and generating random numbers are also covered in this tutorial.
After clearing the basic concepts, the following tutorials in the series will teach you how to use Pytorch for creating and training neural networks of various types such as ANN(Artificial Neural Networks), CNN(Convolutional Neural Networks), RNN(Recurrent Neural Networks) and GAN(Generative Adversarial Networks). Additionally, you will also learn data handling and data pre-processing in Pytorch.
Audience
This Pytorch tutorial is prepared for individuals who are stepping into the field of Deep Learning and want to learn Pytorch as a tool to implement and train neural networks. This tutorial has been designed to take you from scratch to an advanced level from where you will be able to learn even more advanced concepts on your own.
Prerequisites
This tutorial series is designed to get you started in Pytorch. It is however assumed that you have basic knowledge of Python programming and Deep Learning. Additionally, any prior knowledge about Pytorch and numerical computation libraries such as numpy will be helpful.