Archit Kulkarni

Developer, Anyscale

Archit Kulkarni is a software engineer at Anyscale working on the open-source library Ray Serve. Prior to joining Anyscale, Archit completed his PhD in mathematics at UC Berkeley.

Past sessions

Summit 2021 Building an ML Platform with Ray and MLflow

May 27, 2021 03:50 PM PT

A successful machine learning platform allows ML practitioners to focus solely on their experiments and models and minimizes the time it takes to develop ML applications and take them to production. However, building an ML Platform is typically not an easy task due to the many different components involved in the process. In this talk, we will show how two open source projects, Ray (https://ray.io/) and MLflow (https://mlflow.org/), work together to make it easy for ML platform developers to add scaling and experiment management to their platform.

We will first provide an overview of Ray and its native libraries: Ray Tune (https://tune.io) for distributed hyperparameter tuning and Ray Serve (https://docs.ray.io/en/master/serve/index.html) for scalable model serving. Then we will showcase how MLflow provides a perfect solution for managing experiments through integrations with Ray for tracking and model deployment. Finally, we will finish with a demo of an ML platform built on Ray, MLflow, and other open source tools.

In this session watch:
Amog Kamsetty, Developer, Anyscale
Archit Kulkarni, Developer, Anyscale

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