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ML Engineering
Building a model is one thing. Getting it to actually work in the real world is another. Posts on the engineering side of ML — deployment, pipelines, monitoring, and everything that happens after the training is done.
Deep Learning Cheatsheet
The whole of deep learning on one page, explained line by line: tensors and autograd, the training loop, activations and losses, CNNs, RNNs, attention, tuning and deployment.
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