Posts by Jules S. Damji

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03 . 24 . 2022

Large-scale distributed training with TorchX and Ray

We're excited to introduce a new Ray Scheduler for TorchX — a joint effort from the PyTorch and Anyscale teams that allows developers to run scalable and distributed PyTorch workloads without setting up infrastructure or changing training scripts.

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03 . 23 . 2022

Ray Summit 2022 Call for Papers is now open

Ray Summit, the annual Ray user conference, is back this August, and the Call for Papers is open until April 18! In this blog post, we’ll give you all the information you need to prepare a stellar talk proposal.

Fig 2 ml models blog
02 . 04 . 2022

Considerations for deploying machine learning models in production: Part 2

In an earlier blog post, we shared five considerations for deploying machine learning models in production. In this post, we'll explore how to tune and train at scale and track model experiments.

MLPatternsProduction
11 . 16 . 2021

Considerations for Deploying Machine Learning Models in Production

A common grumble among data science or machine learning researchers or practitioners is that putting a model in production is difficult. As a result, some claim that a large percentage, 87%, of models never see the light of the day in production.

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