Practice your PyTorch skills by building key machine learning components from scratch. This tool gives you real coding problems like softmax, attention, and GPT-2. An automated judge checks your code for correctness, gradient compatibility, and speed. It is like LeetCode but for tensors.
You get instant feedback on your work. The problems range from easy to hard. They cover things like ReLU, LayerNorm, and multi-head attention. Each problem has a blank template to start with and a reference solution to study after you try.
You can use this skill online for free or run it locally with Docker. It is perfect for machine learning interview preparation and for improving your understanding of neural network internals.
Global
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mkdir -p .claude/skills/torchcode-pytorch-interview-practiceSource Repository
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