Troubleshooting & Testing - FSDL 2022

YouTube·Deep Learning

Explore essential techniques for troubleshooting and testing machine learning codebases and deep neural networks in this 43-minute lecture from the Full Stack Deep Learning 2022 course. Learn about software testing fundamentals, including tools like pytest, doctests, and codecov, as well as clean code practices using black, flake8, and shellcheck. Discover automation strategies with GitHub Actions, and delve into ML-specific testing approaches for data, training processes, and models. Understand the importance of testing in production and the ML Test Score concept. Gain insights into troubleshooting models and performance issues to enhance your ML development skills.