MLOps Pipeline and Available Tools

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.

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About Chip Huyen

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.