This event is for developers that want to learn more about building machine learning applications at speed and scale.
In the Day 1 sessions and workshops, you'll learn how to quickly add intelligence to any application with API-driven services that provide pre-trained models to enable out of the box computer vision, speech, language analysis, and chatbot functionality. You'll explore a variety of real world use cases to see how these services can add ML to your applications today.
In Day 2, you'll dive into building, training, and deploying machine learning models using popular frameworks such as Apache MXNet and TensorFlow. In these sessions and workshops, you will learn how to qualify framework decisions, explore neural network architectures, and build systems designed for training and inference at massive scale. By the end, you'll have a practical understanding of how to use Amazon SageMaker, AWS's ML platform that makes it easy to build, train, and deploy ML models by eliminating the heavy lifting that traditionally slows down model development.