Amazon SageMaker developer resources

This presentation introduces you the features of Amazon SageMaker, including a one-click training environment, highly-optimized machine learning algorithms with built-in model tuning, and deployment without engineering effort. You'll also hear how and why Intuit is using Amazon SageMaker on AWS for real-time fraud detection. (1:02:07)

Amazon AI algorithms are a collection of distributed streaming ML algorithms that scale to any amount of data. This presentation describes the distributed streaming model and its numerous benefits to machine learning practitioners, as well as how to invoke large scale learning from Amazon SageMaker. (54:08)

This webinar dives deeper into Amazon SageMaker, with demos on using neural networks and embeddings for recommendations, and how you can bring your own R algorithm using the sample Juptyer notebooks to get you started. (30:20)

Walk though an overview of how to build, train and deploy machine learning models on Amazon SageMaker, with AWS Evangelist, Julien Simon. (33:05)

This tech talk introduces you to the collection of distributed streaming ML algorithms that come with Amazon SageMaker. You will learn about the difference between streaming and batch ML algorithms, and how SageMaker has been architected to run these algorithms at scale. We will demo Neural Topic Modeling of text documents using a sample notebook. (30:56)

In this tech talk, you’ll learn how AWS Greengrass and Amazon SageMaker enable you to perform machine learning at the edge. We will focus on various business use cases and a demo of our technologies. (42:16)