- Why: learning Java and wanting to understand AI under the hood
- Tensors and matmul first, then gradient checks for every layer
- Building Conv2D, LSTM and a mini transformer
- Making it small: int8 and int4 quantization
- Testing: 283 tests, including autograd checks
- The PyTorch comparison: same CNNs, same epochs, accuracy within about 1 point
- What I learned and what's next Links: https://github.com/manishn1877/minidl-java/tree/main and https://manishn1877.github.io/minidl-java/
AI & ML
Source:https://dev.to/manishn18/how-i-built-a-deep-learning-library-in-pure-java-and-compared-it-with-pytorch-2j8l
How I built a deep learning library in pure Java (and compared it with PyTorch)
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