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distill.pub | ||
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blog.quipu-strands.com
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blog.fastforwardlabs.com
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| | | | | By Chris and Melanie. The machine learning life cycle is more than data + model = API. We know there is a wealth of subtlety and finesse involved in data cleaning and feature engineering. In the same vein, there is more to model-building than feeding data in and reading off a prediction. ML model building requires thoughtfulness both in terms of which metric to optimize for a given problem, and how best to optimize your model for that metric! | |
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jxmo.io
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| | | | | A primer on variational autoencoders (VAEs) culminating in a PyTorch implementation of a VAE with discrete latents. | |
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www.analyticsvidhya.com
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| | | Explore RNNs: their unique architecture, working principles, BPTT, pros/cons, and Python implementation using Keras. | ||
