Posts in: Blog

FEB 20, 2019

Addressing the challenges of massively parallel hyperparameter optimization

By Ameet Talwalkar, Desmond Chan

As most deep learning engineers know, it can take days or weeks to train a deep learning model, costing organizations considerable time and money. But what if we could speed up the process and achieve better results in the process?

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DEC 18, 2018

What’s the deal with Neural Architecture Search?

By Liam Li, Ameet Talwalkar

Deep learning offers the promise of bypassing the process of manual feature engineering by learning representations in conjunction with statistical models in an end-to-end fashion.

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OCT 16, 2018

Warm starting for efficient deep learning resource utilization

By Jennifer Villa, Yoav Zimmerman

In this post, we discuss how warm-starting can save computational resources and improve generalizability when training deep learning models.

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AUG 30, 2018

Recapping our first Women in Infrastructure meetup

By Jennifer Villa

Last week, we at Determined AI were honored to sponsor a meetup of the Women in Infrastructure group focused on ML infrastructure.

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AUG 20, 2018

Getting the most out of your GPU cluster for deep learning: part II

By Jennifer Villa, Neil Conway

In this post, we discuss the missing key to fully leveraging your hardware investment: specialized software that understands the unique properties of deep learning workloads.

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JUL 25, 2018

Getting the most out of your GPU cluster for deep learning: part I

By Jennifer Villa, Jonathan Ben-tzur

To maximize the value of your deep learning hardware, you’ll need to invest in software infrastructure. Setting up a cluster manager is an essential first step in this process, but it’s not the end of the story.

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MAY 25, 2018

Reproducibility in ML: why it matters and how to achieve it

By Jennifer Villa, Yoav Zimmerman

Reproducible machine learning is hard, particularly when training deep learning models. We review common sources of DL non-determinism and how to address them.

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APR 25, 2018

Toward the Jet Age of machine learning

By Ameet Talwalkar

Machine learning today resembles the dawn of aviation.

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