Explore testing and deployment strategies for machine learning projects in this comprehensive lecture from the Full Stack Deep Learning March 2019 bootcamp. Delve into topics such as project structure, AB testing, evaluation methods, continuous integration, and software services. Learn about deployment options including virtual machines, Docker containers, REST APIs, and serverless architectures. Discover best practices for load balancing, dependency management, and handling distribution shifts. Gain insights on CPU-only, batch, and algorithmic deployment techniques, as well as strategies for rollbacks and optimizing startup times.