Quality Assurance and Machine Learning Model Validation

Explore the critical process of quality assurance and machine learning model validation in this 45-minute conference talk from the Data Science Festival Summer School 2021. Delve into the essential steps following data wrangling, exploratory analysis, and model selection. Learn how to navigate the crucial QA stage, addressing key concerns such as bias and data leaks. Gain valuable insights from Raluca Crisan, Data Scientist and Co-Founder of ETIQ, as she provides a high-level overview of this vital component in the MLOps process. Discover best practices for model review, whether working in small teams with code reviews or larger teams with established testing protocols. Enhance your understanding of the final stages in machine learning model development and ensure the reliability and effectiveness of your data science projects.