Overview
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Explore LinkedIn's approach to scaling AI and ML systems in this 51-minute conference talk from Devoxx Poland 2019. Discover how LinkedIn has been applying AI in their products for over a decade and learn about their efforts to improve ML engineering productivity. Gain insights into their framework designed to provide an excellent developer experience across all phases of the ML workflow, including exploration, authoring, training, deployment, and production. Delve into topics such as the Feature Marketplace, Quasar Inference Library, Pro-ML Jupyter Notebook, Gradle plugins, and the Model Explorer. Understand LinkedIn's vision for making ML accessible to engineers across all product groups and their ongoing work to enhance ML productivity.
Syllabus
Intro
Why this ML talk?
2016 - "Go" game
2019 - Starcraft 2
Recruiter search
ML opportunities
What is ML productivity?
Measuring productivity
Feature marketplace
Quasar: Inference Library
Pro-ML Jupyter Notebook
Gradle plugins
Model explorer
Work in progress
Taught by
Devoxx