Brancher vs Grooper: What are the differences?

Developers describe Brancher as "A Python package for differentiable probabilistic inference". It is a user-centered Python package for differentiable probabilistic inference. It allows to design and train differentiable Bayesian models using stochastic variational inference. It is based on the deep learning framework PyTorch. On the other hand, Grooper is detailed as "Innovate workflows by integrating difficult data". It empowers rapid innovation for organizations processing and integrating large quantities of difficult data. Created by a team of courageous developers frustrated by limitations in existing solutions, It is an intelligent document and digital data integration platform. It combines patented and sophisticated image processing, capture technology, machine learning, and natural language processing.

Brancher and Grooper can be categorized as "Data Science" tools.

Brancher is an open source tool with 187 GitHub stars and 30 GitHub forks. Here's a link to Brancher's open source repository on GitHub.