A carefully curated collection of high-quality libraries, projects, tutorials, research papers, and other essential resources focused on TinyML — the intersection of machine learning and ...

This is the Python material that does not get left behind. Almost none of it is replaced by a framework later. Learn it, and keep this cheat sheet close by as a handy reference.

When it comes to removing Burmese pythons, one snake does not equal another. A new study by researchers at the University of ...

Introduction A few years ago, I took over a demand forecasting model from a colleague who had left the company. The notebook ...

Overview:  Python’s extensive ecosystem supports everything from data preparation to model training. Go takes a different ...

Introduction A few years ago, I was in charge of demand forecasting models at my company. Even though the accuracy was decent ...

Slicing bytes copies. On a small payload nobody notices, but slice a large packet or image buffer in a loop and the copies ...

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Urban heat islands are a solvable data problem: this piece shows how to combine free satellite imagery, standard ...

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Overview:  Deep learning uses multi-layer neural networks to learn patterns from data.CNNs, RNNs, LSTMs, transformers, and autoencoders support different t ...