Basic Pytorch Tensor Manipulation for Machine Learning
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Learn the basics of tensor manipulation in PyTorch for machine learning applications, focusing on practical examples and techniques.
Tensors form the fundamental building block of the PyTorch ecosystem. Various components, such as network layers, loss function, gradient descent, and optimizer rely on underlying tensor operations.
In this course, you will get a comprehensive overview of tensors starting with how to create one. You will learn the many different types of tensors as well as how to concatenate and manipulate them by selecting elements, changing the shape, and more.
By the end of this course, you will have a basic understanding of how to work with PyTorch tensors and what they allow you to do.
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