Productizing ML at Scale at Twitter with Yi Zhuang
EPISODE 271
|
JUNE
3,
2019
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About this Episode
Today we continue our AI Platforms series joined by Yi Zhuang, Senior Staff Engineer at Twitter & Tech Lead for Machine Learning Core Environment at Twitter Cortex.
In our conversation, Yi guides us through the machine learning landscape at Twitter, starting with the history of the Cortex team, who are responsible for building and maintaining their ML platform. We dig into their recently released Deepbird v2 framework, which is used for model training and evaluation solutions, and it's integration with Tensorflow 2.0. We also discuss their efforts in automating hyperparameter searches, pipeline management, and their newly assembled "Meta" team, that is tasked with exploring the bias, fairness, and accountability of their machine learning models.
About the Guest
Yi Zhuang
stakefish
Resources
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- History of Twitter Cortex - Acquisition of Madbits, Whetlab, and MagicPony
- DeepBird V2 - Twitter's new machine learning platform based on TensorFlow
- Productionizing Machine Learning with ML Workflows at Twitter
- Using Deep Learning for Ranking Tweets on the home timeline
- Click-through prediction for Advertising in Twitter Timeline
- Twitter Search Ranking: Moving Top Tweet Search Results from Reverse Chronological Order
- Speedy Neural Networks for Smart Auto-Cropping of Images
- Ranking Tweets with TensorFlow
- Unifying Twitter around a single ML platform - Slides
- TWIML Presents: AI Platforms Vol. 1
