Explore the importance of continuous validation in machine learning models and learn best practices for integrating automated testing into CI/CD pipelines. Discover common pitfalls in ML model development and how to overcome them using the deepchecks open source package. Gain insights from Shir Chorev, co-founder and CTO of Deepchecks, as she shares her expertise on validating models and data during research and CI/CD phases. Understand the challenges of testing models with constantly changing data and black-box logic, and learn how to ensure your models remain relevant and trustworthy in production environments. This 48-minute talk from Data Council provides valuable knowledge for data professionals looking to enhance their ML model testing and validation processes.