Explore real-time stream processing for machine learning in this 28-minute talk by Alejandro Saucedo from The Institute for Ethical AI & Machine Learning. Dive into the evolution of ETL processes, compare batch vs streaming approaches, and understand key streaming concepts like windows, checkpoints, and watermans. Learn about machine learning workflows, model pipeline components, and feature engineering. Examine architecture overviews for Kubernetes, discussing horizontal and vertical scalability. Gain insights into native service orchestration integration beyond REST and API protocols. Access code examples and relevant links to enhance your understanding of implementing machine learning in real-time streaming environments.