Machine Learning Design Patterns - Model Monitoring and Explainable Predictions

Explore two essential machine learning design patterns in this 39-minute conference talk from the Toronto Machine Learning Series (TMLS). Join Michael Munn, ML Solutions Engineer at Google, as he delves into the best practices and solutions for recurring problems in machine learning. Focus on the detailed discussion of two tried-and-proven methods: Model Monitoring and Explainable Predictions. Gain valuable insights from the recently released O'Reilly book "Machine Learning Design Patterns," which covers thirty design patterns across various stages of the machine learning process. Enhance your understanding of effective strategies to improve your machine learning projects and overcome common challenges in the field.