AWS SageMaker Workshop at Yale Center for Research Computing
Date: September 18, 2018
Time: 1pm - 4pm
Presenter: Nick Ragusa, AWS Solutions Architect
This workshop will walk you through the process of building a model, training it, and applying it for prediction. Working in web-based Jupyter Notebooks powered by AWS, we'll explore a cloud-first paradigm for common algorithms (e.g. k-means and PCA) and deep learning with MXNet and TensorFlow. Participants will also become familiar with SDKs for Python and Spark, as well as other APIs that make machine learning with AWS easy to use. You will experiment on real-world datasets offered in the AWS Open Data program, such as Earth on AWS and the Cancer Genome Atlas. At the end of the session, you will have the knowledge to start using Amazon SageMaker and other AWS services for your own scientific research.
Agenda:
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Introduction to AWS SageMaker
- Typical machine learning lifecycle - get data, train model, deploy model
- Walk through of environment set-up & build simple model
- Public data sets on AWS
- Going beyond, facilitating SDKs & APIs
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