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Productive Machine Learning at LinkedIn with Bee-Chung Chen - TWiML Talk #200

Productive Machine Learning at LinkedIn with Bee-Chung Chen - TWiML Talk #200

FromThe TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)


Productive Machine Learning at LinkedIn with Bee-Chung Chen - TWiML Talk #200

FromThe TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)

ratings:
Length:
48 minutes
Released:
Nov 15, 2018
Format:
Podcast episode

Description

In this episode of our AI Platforms series, we’re joined by Bee-Chung Chen, Principal Staff Engineer and Applied Researcher at LinkedIn. Bee-Chung and I caught up to discuss LinkedIn’s internal AI automation platform, Pro-ML, which was built with the hopes of providing a single platform for the entire lifecycle of developing, training, deploying, and testing machine learning models. In our conversation, Bee-Chung details Pro-ML, breaking down some of the major pieces of the pipeline including their feature marketplace, model creation tooling, and training management system to name a few. We also discuss LinkedIn’s experience bringing Pro-ML to the company's developers and the role the LinkedIn AI Academy plays in helping them get up to speed. For the complete show notes, visit https://twimlai.com/talk/200. For more information about the AI Platforms series, visit https://twimlai.com/aiplatforms. Be sure to sign up for our newsletter at https://twimlai.com/newsletter.
Released:
Nov 15, 2018
Format:
Podcast episode

Titles in the series (100)

This Week in Machine Learning & AI is the most popular podcast of its kind. TWiML & AI caters to a highly-targeted audience of machine learning & AI enthusiasts. They are data scientists, developers, founders, CTOs, engineers, architects, IT & product leaders, as well as tech-savvy business leaders. These creators, builders, makers and influencers value TWiML as an authentic, trusted and insightful guide to all that’s interesting and important in the world of machine learning and AI. Technologies covered include: machine learning, artificial intelligence, deep learning, natural language processing, neural networks, analytics, deep learning and more.