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.

Microsoft Azure Event Hubs checkpointer implementation with Blob Storage Client Library for Python

An accurate and scalable semi-supervised deep learning method for imputing dropouts for single-cell transcriptome

Implementation of the ToMATo clustering algorithm, with clique complex and KNN nearest neighbors graph.

Converting ADAMS annotations to tfrecords.

An implementation of the Anchor Graph Hashing algorithm (AGH-1), presented in Hashing with Graphs (Liu et al. 2011).

Text Embeddings for ClowdFlows

practice for K-Means algorithm

Condensa Programmable Model Compression Framework. Condensa is a framework for _programmable model compression_ in Python. It comes with a set of built-in compression operators which may be used to compose complex compression schemes targeting specific combinations of DNN architecture, hardware platform, and optimization objective. To recover any accuracy lost during compression, Condensa uses a constrained optimization formulation of model compression and employs an Augmented Lagrangian-based algorithm as the optimizer.

CoreNLG is an easy to use and productivity oriented Python library for Natural Language Generation. It aims to provide the essential tools for developers to structure and write NLG projects. Auto-agreement tools based on extra-resources are not provided in this library.

ERRor ANnotation Toolkit: Automatically extract and classify grammatical errors in parallel original and corrected sentences.