Build, Train, and Deploy ML Models at Scale with Amazon SageMaker

Location:  IDRE Portal (5628 Math Science Building)
Wednesday, August 22, 2018 - 10:00am to 1:00pm

Event: Build, Train, and Deploy ML Models at Scale with Amazon SageMaker

Date: August 22, 2018

Time: 10:00AM - 1:00PM

Food: Pizza will be served

Location: IDRE Portal

Description: Build, Train and Deploy ML Models at Scale with Amazon SageMaker

In this tutorial participants learn to solve Machine / Deep Learning problems using the tools available in the Amazon Web Services (AWS) cloud. The development and application of machine learning models is a vital part of scientific and technical computing. Increasing model training data size generally improves model prediction and performance, but deploying models at scale is a challenge. Participants will learn to use Amazon SageMaker, a new AWS service that simplifies the machine learning process and enables training on cloud stored datasets at any scale.

Applications will include:

  • satellite imagery, MXNet, LandSat dataset : automatically mapping buildings in Vietnam
  • chemistry, DeepChem: building an online compound solubility prediction workflow
  • genomics, 1000 genomes dataset

The tutorial will walk attendees 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 common algorithms (e.g. k-means and PCA) and deep learning with MXNet and TensorFlow. Participants will become familiar with SDKs for Python and Spark and other APIs that make machine learning with AWS easy to use. With Amazon SageMaker, users take their code and analysis to the data, and participants will experiment on real-world datasets, such as Earth on AWS and the Cancer Genome Atlas. At the end of the session, attendees will have the resources and experience to start using Amazon SageMaker and other AWS services to accelerate their scientific research and time to discovery.


Intended audience

Machine Learning Practitioners old and new: developers, scientists, data science practitioners, research staff, and any other interested persons. Participants should have some familiarity with:

  • python
  • jupyter notebooks
  • basic machine learning methods

RSVP by submitting a registration form through the Sign Up Now button above.