Scanning all new published packages on PyPI I know that the quality is often quite bad. I try to filter out the worst ones and list here the ones which might be worth a look, being followed or inspire you in some way.

A fast and covariate-adaptive method for multiple hypothesis testing

A straightforward package for linear regression with Gaussian priors.

KenLM decoder for Non-Autoregressive Models.

event sourcing for databases.

Generic neural networks high level wrapper for PyTorch

Library for probabilistic predictions via gradient boosting.

numba-scipy extends Numba to make it aware of SciPy

The numpy-financial package contains a collection of elementary financial functions.

Tensorflow Object Detection Library

olr: Optimal Linear Regression. The olr function runs all the possible combinations of linear regressions with all of the dependent variables against the independent variable and returns the statistical summary of either the greatest adjusted R-squared or R-squared term.

PyTorch Optimization Framework for Researchers

Monitor status, security, and robustness of your machines. Basically, there are lots of little monitoring and checking tasks you may find yourself needing to do. You could write a separate script for each such task, but it would be nice to have some basic scaffolding for things like notifications, logging, testing, and so on to simplify machine monitoring. Better yet, by having a common framework many developers can contribute small snippets of such tools that work in a similar way to simplify life for everyone.

Set of utilities for ploting results of non-deterministic experiments, e.g. machine learning, optimization, genetic algorithms. Pen’n’paper is a package to easily collect the data about (noisy) processes and plot them for comparison. This package is not aiming at feature completeness. Instead it should give you an easy start during the phase of the project when you want to just concentrate on an experimental idea.

A Toolkit for Reinforcement Learning in Card Games

A package to check system related metrics and values for simpler blackbox monitoring