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:
A good starting material to understand the mechanics of tensors before moving on to models and training.▶️ What tensors are and why they are needed▶️ 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
tags: #useful
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