A collection of basic techniques for working with tensors in PyTorch — for those who are starting to get acquainted with the framework and want to quickly master its fundamentals.
What's inside:
▶️ What tensors are and why they are neededA good starting material to understand the mechanics of tensors before moving on to models and training.
▶️ Tensor initialization: zeros, ones, random, similar size
▶️ Type conversion and switching between NumPy and PyTorch
▶️ Arithmetic, logical operations, tensor comparison
▶️ Matrix multiplication and batch computations
▶️ Broadcasting, view(), reshape(), changing dimensions
▶️ Indexing and slicing: how to access parts of a tensor
▶️ Notebook with code examples
⛓ GitHub link
tags: #useful
➡ @codeprogrammer