This is suite of the hands-on training materials that shows how to scale CV, NLP, time-series forecasting workloads with Ray.

This repository showcases hands-on projects leveraging distributed multi-GPU training to fine-tune large language models (LLMs).

Analyzing sentiment from Twitter data presents key challenges, including handling large-scale, noisy text and the absence of labeled data. This project addresses these issues through a two-phase pipeline.

Encoder-Decoder model for pinterest image recommender system using active learning. Built with PyTorch and Ray

This MLOps repository contains python modules intended for distributed model training, tuning, and serving using PyTorch and Ray, a distributed computing framework.