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Chapter 1

The PyTorch Basics notebook contains many of the examples below, but not all.

In Text Examples

Example 1-1. Generating a “collapsed” one-hot or binary representation using scikitlearn
Example 1-2. Generating a TF-IDF representation using scikit-learn
Example 1-3. Creating a tensor in PyTorch with torch.Tensor
Example 1-4. Creating a randomly initialized tensor
Example 1-5. Creating a filled tensor
Example 1-6. Creating and initializing a tensor from lists
Example 1-7. Creating and initializing a tensor from NumPy
Example 1-8. Tensor properties
Example 1-9. Tensor operations: addition
Example 1-10. Dimension-based tensor operations
Example 1-11. Slicing and indexing a tensor
Example 1-12. Complex indexing: noncontiguous indexing of a tensor
Example 1-13. Concatenating tensors
Example 1-14. Linear algebra on tensors: multiplication
Example 1-15. Creating tensors for gradient bookkeeping
Example 1-16. Creating CUDA tensors
Example 1-17. Mixing CUDA tensors with CPU-bound tensors