lukasmasuch/best-of-ml-python

Best-of Machine Learning with Python is a curated, ranked directory of open-source Python libraries for machine learning. Rather than being a piece of software you run, it is a reference list: a regularly updated catalogue of 920 projects organized into 34 categories, covering areas like machine learning frameworks, data visualization, natural language processing, image processing, audio analysis, time series, reinforcement learning, AutoML, model deployment, and more. Each entry is ranked by a quality score that is automatically calculated from GitHub metrics (stars, contributors, forks, update frequency) and package manager download data. Visual indicators show whether a project is new, trending, inactive, or potentially abandoned, helping you quickly judge whether a library is worth adopting. Projects are also tagged by which major framework they relate to, such as PyTorch, TensorFlow, or scikit-learn. You would use this list when you need to find the right Python library for a machine learning task, for example, looking for the best tool for hyperparameter tuning, or comparing options for serving a model in production. It is especially useful for data scientists and developers who want a quick, opinionated starting point rather than sifting through thousands of GitHub repositories themselves. The list is updated weekly.