Chip Huyen

ML Engineer and Open Source Lead, Snorkel AI

Chip Huyen works to bring the best practices to machine learning production. She’s built AI applications at Snorkel AI, Netflix, NVIDIA, and Primer. She graduated from Stanford, where she taught TensorFlow for Deep Learning Research. She’s also the author of four bestselling Vietnamese books.

Past sessions

MLOps Pipeline and Available Tools

November 18, 2020 04:00 PM PT

The first part of the talk covers the four main stages in the iterative process of ML systems design. For each stage, it breaks down the steps needed, the tradeoffs of different solutions at each step, and available tools. The goal of this part is to help people interested in ML in the industry understand what it means to bring ML into production.

The next part surveys the MLOps landscape by analyzing over 200 tools. Many companies claim to provide end-to-end platforms/solutions, while covering only a small number of steps in this process. This part helps users understand where each tool fits into the pipeline and evaluate which works best for them.

Summit Europe 2020 Principles of Good Machine Learning Systems Design

November 18, 2020 04:00 PM PT

This talk covers what it means to operationalize ML models. It starts by analyzing the difference between ML in research vs. in production, ML systems vs. traditional software, as well as myths about ML production.

It then goes over the principles of good ML systems design and introduces an iterative framework for ML systems design, from scoping the project, data management, model development, deployment, maintenance, to business analysis. It covers the differences between DataOps, ML Engineering, MLOps, and data science, and where each fits into the framework.

The talk ends with a survey of the ML production ecosystem, the economics of open source, and open-core businesses.

Speaker: Chip Huyen