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.

ABOUT THE AUTHOR

Neko Yan

Data lovers, machine learning enthusiasts. Senior machine learning researcher in NLP, reinforcement learning, and display advertisement prediction.

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Tensor manipulation is crucial in Deep Learning (DL), and this course teaches efficient techniques for handling tensors.

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