Posts by Amog Kamsetty

Ray Train
01 . 25 . 2022

Distributed deep learning with Ray Train is now in Beta

Introducing Ray Train, an easy-to-use library for distributed deep learning. In this post, we show how Ray Train improves developer velocity, is production-ready, and comes with batteries included.

forecasting blog 2 of 2 image 1
12 . 21 . 2021

Time Series Forecasting using an LSTM version of RNN with PyTorch Forecasting and Torch Lightning

This blog, Part 2, will explain how to use Ray to speed up Deep Learning forecasting when training one large global model in order to predict many target time series. We will train an LSTM version of RNN with GRN building blocks, Encoder-Decoder, and...

Ray Lightning
08 . 19 . 2021

Introducing Ray Lightning: Multi-node PyTorch Lightning training made easy

Ray Lightning is a new plugin that makes running multi-node GPU training with PyTorch Lightning fast and easy.

XGBoost-Ray
06 . 16 . 2021

Introducing Distributed XGBoost Training with Ray

XGBoost-Ray is a novel backend for distributed XGBoost training. It features multi node and multi GPU training, distributed data loading, advanced fault tolerance such as elastic training, and a seamless integration with hyperparameter optimization f...

RAG
02 . 10 . 2021

Retrieval Augmented Generation with Huggingface Transformers and Ray

Huggingface Transformers recently added the Retrieval Augmented Generation (RAG) model, a new NLP architecture that leverages external documents (like Wikipedia) to augment its knowledge and achieve state of the art results on knowledge-intensive tas...

Ray x mlflow
01 . 13 . 2021

Ray & MLflow: Taking Distributed Machine Learning Applications to Production

In this blog post, we're announcing two new integrations with Ray and MLflow: Ray Tune+MLflow Tracking and Ray Serve+MLflow Models, which together make it much easier to build ML models and take them to production.

Pb2: Solo Gif
11 . 16 . 2020

Population Based Bandits: Provably Efficient Online Hyperparameter Optimization