FedFA

A curated list of references for MLOps

Perform data science on data that remains in someone else's server

A system for quickly generating training data with weak supervision

A GPU-accelerated library containing highly optimized building blocks and an execution engine for data processing to accelerate deep learning training and inference applications.

FEDML - The unified and scalable ML library for large-scale distributed training, model serving, and federated learning. FEDML Launch, a cross-cloud scheduler, further enables running any AI jobs on any GPU cloud or on-premise cluster. Built on this library, TensorOpera AI (https://TensorOpera.ai) is your generative AI platform at scale.

Version control that works the way you think

TextAttack ? is a Python framework for adversarial attacks, data augmentation, and model training in NLP https://textattack.readthedocs.io/en/master/

A high-performance Python-based I/O system for large (and small) deep learning problems, with strong support for PyTorch.

A Python library for audio data augmentation. Useful for making audio ML models work well in the real world, not just in the lab.

A PyTorch implementation for exploring deep and shallow knowledge distillation (KD) experiments with flexibility