Machine Learning Design Patterns


Jan 19, 10:30 AM PST
  • Virtual AICamp
  • 441 RSVPs
Description
Design patterns capture best practices and solutions to recurring problems. Join us for the tech talks and Q&As, by the authors of the newly released O’Reilly book “Machine Learning Design Patterns”, covering solutions to common challenges in Data Preparation, Model Building, and MLOps.

Lak, Sara and Michael will introduce three of these tried-and-proven methods to help engineers tackle problems that frequently crop up during the ML process. They will dive into the pattern: a description of the problem, a variety of potential solutions, and recommendations for choosing the best technique for your situation.

Talk #1: Data Representation Design Pattern: Embeddings, by Valliappa Lakshmanan
Talk #2: Reproducibility Design Pattern: Model Versioning, by Sara Robinson
Talk #3: Problem Representation Design Pattern: Multilabel, by Michael Munn

We will raffle for the 5 copies of the book (Link) (for the 5 winners: hard copy ship to you if you are within USA; e-copy if you are outside of USA).


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