easyocr 1.7.1

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.

HuggingFace community-driven open-source library of datasets

AutoML for Image, Text, and Tabular Data

An efficient library for image augmentation, providing extensive transformations to support machine learning and computer vision tasks.

Text utilities and datasets for PyTorch

State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow

A refreshing functional take on deep learning, compatible with your favorite libraries

HuggingFace/NLP is an open library of NLP datasets.

Keras is a deep learning API written in Python, running on top of the machine learning platform TensorFlow. The core data structures of Keras are layers and models. The philosophy is to keep simple things simple, while allowing the user to be fully in control when they need to (the ultimate control being the easy extensibility of the source code via subclassing).