Organizations are using machine learning to address a series of business challenges, ranging from product recommendations, demand forecasting, customer churn, medical research, and many more. The ML process includes framing the problem statement, collecting and preparing data, training and tuning, and deploying the models. In this session, Vlad Zhukov, Head of Engineering for Amazon SageMaker, talks about how SageMaker removes the barriers and complexity associated with building, training, and deploying ML models at scale to address a wide range of use cases.