Project: Linear regression using pytorch

Predictive modeling with deep learning

It is a skill that modern developers need to know. PyTorch is the premier open-source deep learning framework developed and maintained by Facebook. At its core, PyTorch is a mathematical library that allows you to perform efficient computation and automatic differentiation on graph-based models. Achieving this directly is challenging, although thankfully, the modern PyTorch API provides classes and idioms that allow you to easily develop a suite of deep learning models. In this tutorial, you will discover a step-by-step guide to developing deep learning models in PyTorch.

After completing this tutorial, you will know:

• The difference between Torch and PyTorch and how to install and confirm PyTorch is working.
• The five-step life-cycle of PyTorch models and how to define, fit, and evaluate models.

• How to develop PyTorch deep learning models for regression, classification, and predictive modeling tasks.

  Summary

  In this tutorial, you discovered a step-by-step guide to developing deep learning models in PyTorch. Specifically, you learned:

• The difference between Torch and PyTorch and how to install and confirm PyTorch is working.
• The five-step life-cycle of PyTorch models and how to define, fit, and evaluate models.

• How to develop PyTorch deep learning models for regression, classification, and predictive modeling tasks.

  Link

• https://jovian.ml/garimasingh128/project/v/1?utm_source=embed