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Tensor Puzzles is an interactive collection of 21 exercises for learning tensor programming in PyTorch and NumPy. Each puzzle asks the learner to recreate a familiar array operation from first principles. Solutions must fit on one short line and use only a restricted set of indexing, arithmetic, comparison, and broadcasting tools. Standard convenience functions such as sum, view, squeeze, and take are intentionally prohibited. This constraint encourages a deeper understanding of shapes, indexing, and vectorized computation. Automated tests and visual examples help learners check their reasoning as they progress. The notebook is designed for Google Colab and is accompanied by a video walkthrough.
Features
- Twenty-one tensor programming puzzles
- PyTorch and NumPy exercises
- Broadcasting-focused problem solving
- Restricted one-line solutions
- Automated tests and visual examples
- Google Colab and video walkthrough
Project Samples
Categories
Machine LearningLicense
MIT LicenseFollow Tensor Puzzles
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