Using PyTorch in Python: An Introduction to Machine Learning and Deep Learning

PyTorch is an open-source machine learning library developed by Facebook’s AI Research lab (FAIR) that provides a flexible and efficient platform for building deep learning models. In this article, we will explore the basics of PyTorch and its application in Python.

Table of Contents

1. Introduction to PyTorch
2. Installation and Setup
3. Tensors
4. Autograd
5. Creating a Neural Network
6. Training a Neural Network
7. Conclusion

Introduction to PyTorch

PyTorch is a powerful library that offers a dynamic computation graph and GPU acceleration, making it suitable for a wide range of machine learning and deep learning tasks. PyTorch allows you to create and train complex models using an easy-to-understand Pythonic syntax.

Some key features of PyTorch are:

• Tensor computation: PyTorch provides a multi-dimensional array called a tensor, which can be used for various mathematical operations.
• GPU acceleration: PyTorch supports NVIDIA’s CUDA platform, allowing tensors to be stored and operated on using GPU…