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1. Find a paper you like/admire 2. Implement their methods from scratch (i.e. numpy not pytorch) 3. Experiment a bit, tweaking the models/algs to gain intuiti
by boltzmannbrain 7y ago
1. Find a paper you like/admire
2. Implement their methods from scratch (i.e. numpy not pytorch)
3. Experiment a bit, tweaking the models/algs to gain intuition
4. Repeat 1-3
- throwlaplace 7y ago> Implement their methods from scratch (i.e. numpy not pytorch) lol this is basically impossible and completely pointless. please show me a numpy implementation of BERT or CycleGAN or deformable convolutions (note that jax != numpy). it's like suggesting implementing a kernel to someone who wants to learn about virtual memory or scheduling. better advice would be take a paper and implement the model using pytorch without looking at their implementation and fiddle with that.