Martin Gorner
Developer Advocate, Google

Martin Gorner is a developer advocate at Google, where he focuses on parallel processing and machine learning. Martin is passionate about science, technology, coding, algorithms, and everything in between. He spent his first engineering years in the Computer Architecture Group of ST Microelectronics, then spent the next 11 years shaping the nascent ebook market at Mobipocket, which later became the software part of the Amazon Kindle and its mobile variants. He’s the author of the successful TensorFlow Without a PhD series. He graduated from Mines Paris Tech.

Sessions

1:30pm–5:00pm Tuesday, October 29, 2019

Location: Grand Ballroom H

Recurrent neural networks without a PhD

Core technologies

Martin Gorner (Google)

Average rating:

(5.00, 3 ratings)

Many problems deemed "impossible" only five years ago have now been solved by deep learning—from playing Go to recognizing what’s in an image to translating languages. Martin Gorner leads a hands-on introduction to recurrent neural networks and TensorFlow. Join in to discover what makes RNNs so powerful for time series analysis. Read more.

2:30pm–3:10pm Wednesday, October 30, 2019

Location: Grand Ballroom H

Fast and lean data science with TPUs

Accelerators

Martin Gorner (Google)

Average rating:

(4.00, 1 rating)

Neural networks are now shipping in consumer-facing projects. Enterprises need to train and ship them fast, and data scientists want to waste less time on endless training. Martin Gorner explains how Google's tensor processing units (TPUs) are here to help. Read more.