facets-overview 1.1.1

A faster way to build and share data apps

Recognize faces from Python or from the command line

This package contains several methods for calculating Conditional Average Treatment Effects

End-to-End Multi-Lingual Optical Character Recognition (OCR) Solution

A Python 3 library for sci-kit learn, XGBoost, LightGBM, Spark, and TensorFlow decision tree visualization

DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions

Haiku is a library for building neural networks in JAX.

A toolkit for making real world machine learning and data analysis applications

DeepSpeed is a Python package developed by Microsoft that provides a deep learning optimization library designed to scale across multiple GPUs and servers. It is capable of training models with billions or even trillions of parameters, achieving excellent system throughput and efficiently scaling to thousands of GPUs.

DeepSpeed is particularly useful for training and inference of large language models, and it falls under the category of Machine Learning Frameworks and Libraries. It is designed to work with PyTorch and offers system innovations such as Zero Redundancy Optimizer (ZeRO), 3D parallelism, and model-parallelism to enable efficient training of large models.