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Machine Learning Platform for Online Prediction and Continual Learning

Posted Apr 12, 2022 | Views 766
# Data engineering
# Explainability and Observability
# Feature Stores
# Research
# Systems and Architecture
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SPEAKER
Chip Huyen
Chip Huyen
Chip Huyen
Co-Founder & CEO @ Claypot AI

Chip Huyen is an engineer who develops tools and best practices for machine learning production. She recently developed Claypot AI, a platform that leverages both batch and streaming systems for real-time machine learning. Through her work with Snorkel AI, NVIDIA, and Netflix, she has helped some of the worldÕs largest organizations deploy machine learning systems. She teaches "CS 329S: ML Systems Design" at Stanford. SheÕs also published four bestselling Vietnamese books and author of "Designing Machine Learning Systems" (OÕReilly, 2022).

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Chip Huyen is an engineer who develops tools and best practices for machine learning production. She recently developed Claypot AI, a platform that leverages both batch and streaming systems for real-time machine learning. Through her work with Snorkel AI, NVIDIA, and Netflix, she has helped some of the worldÕs largest organizations deploy machine learning systems. She teaches "CS 329S: ML Systems Design" at Stanford. SheÕs also published four bestselling Vietnamese books and author of "Designing Machine Learning Systems" (OÕReilly, 2022).

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SUMMARY

This talk breaks down stage-by-stage requirements and challenges for online prediction and fully automated, on-demand continual learning. WeÕll also discuss key design decisions a company might face when building or adopting a machine learning platform for online prediction and continual learning use cases.

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