This course introduces you to PyTorch and focuses on two main concepts: PyTorch tensors and the autograd module. We are going to get our hands dirty throughout the course, using a demo environment to explore the methodologies covered. We'll look at the pros and cons of each method, and when they should be used.
Learning Objectives
Create a tensor in PyTorch
Understand when to use the autograd attribute
Create a dataset in PyTorch
Understand what backpropagation is and why it is important
Intended Audience
This course is intended for anyone interested in machine learning, and especially for data scientists and data engineers.
Prerequisites
To follow along with this course, you should have PyTorch version 1.5 or later.
Resources
The Python scripts used in this course can be found in the GitHub repo here:https://github.com/cloudacademy/ca-pytorch-101

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