Presentation: Tooling & Setup for My Neural Network

Track: Hands-on Codelabs & Speakers Office Hours

Location: Mission

Duration: 2:25pm - 2:35pm

Day of week: Tuesday

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Abstract

I have trained various models over hundreds of training runs and came to two conclusions:

1) waiting for results is not fun

2) waiting and then NOT seeing any results even less so...

A proper toolset is needed if you want to deliver on ML projects where training runs take day(s). I would like to share with you the toolset that I use, both to run multiple training experiments in parallel and visualize their outcomes: Tensorflow, Google Cloud ML Engine, Tensorboard.

Note: This is a short talk. Short talks are 10-minute talks designed to offer breadth across the areas of machine learning, artificial intelligence, and data engineering. The short talks are focused on the tools and practices of data science with an eye towards the software engineer.

Speaker: Martin Gorner

Parallel processing and machine learning @Google

Martin is passionate about science, technology, coding, algorithms and everything in between. He graduated from Mines Paris Tech with a major in computer vision, enjoyed his first engineering years in the computer architecture group of ST Microlectronics and then spent the next 11 years shaping the nascent eBook market, starting with the Mobipocket startup, which later became the software part of the Amazon Kindle and its mobile variants. He joined Google Developer Relations in 2011 and now focuses on parallel processing and machine learning (Dataflow and Tensorflow).

Find Martin Gorner at

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