libraries

Public Hello World to get used to Python and GPT-3 Link

PyTorch Lightning & Lightning Hydra Template are neat. Tensor Puzzles is great intro. TorchScale is nice library for making Transformers efficiently. BackPACK is interesting too. Link

PyTorch deep learning project made easy. Link

A Guide to Isolating and Managing your Machine Learning Models in a Django Framework Link

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LIGHTNING TRANSFORMERS documentation Link

Sketch is an AI code-writing assistant for pandas users that understands the context of your data, greatly improving the relevance of suggestions. Sketch is usable in seconds and doesn’t require adding a plugin to your IDE. Link

Whisper is a general-purpose speech recognition model. It is trained on a large dataset of diverse audio and is also a multi-task model that can perform multilingual speech recognition as well as speech translation and language identification. Link

A machine learning library for unsupervised time series anomaly detection. Link

Have you ever wondered where your lengthy processing was, and when it would finish? Ever found yourself hitting [RETURN] now and then to ensure it didn’t hang, or if, in a remote SSH session, the connection was still working? Ever needed to pause some processing for a while, return to the Python prompt for a manual inspection or fixing an item, and then resume the process seamlessly? Link

Data Science Cookie Cutter Link Article

The Rich API makes it easy to add color and style to terminal output. Rich can also render pretty tables, progress bars, markdown, syntax highlighted source code, tracebacks, and more — out of the box. Link

Learning representations of algorithms is an emerging area of machine learning, seeking to bridge concepts from neural networks with classical algorithms. The CLRS Algorithmic Reasoning Benchmark (CLRS) consolidates and extends previous work toward evaluation algorithmic reasoning by providing a suite of implementations of classical algorithms. These algorithms have been selected from the third edition of the standard Introduction to Algorithms by Cormen, Leiserson, Rivest and Stein. Link

We are excited to present this year’s picks for the most innovative developments in the Python ecosystem. From this edition, we are expanding our list to include not only libraries per-se, but also tools that are built to belong in the Python ecosystem — some of which are not written in Python as you’ll see. Link

Torchview provides visualization of pytorch models in the form of visual graphs. Visualization includes tensors, modules, torch.functions and info such as input/output shapes. Link