Data Science and Machine Learning

Data science and machine learning continue to evolve rapidly, pushing the boundaries of what can be achieved with algorithms, data, and computation. This track will delve into the latest trends, methodologies, and best practices across topics, including advanced algorithmic techniques, model selection, hyperparameter tuning, and the application of machine learning to solve complex business problems. Experts will also share insights on how to operationalize data science workflows, from experiment tracking and reproducibility to deploying models in production environments, aiming to bridge the gap between cutting-edge research and real-world applications.