Oct 8, 2018–Oct 8, 2018 from 9:30am–12:30pm
AWS Seminar Series at Qualcomm Institute
SAGEMAKER WORKSHOP – BUILD, TRAIN AND DEPLOY ML MODELS AT SCALE WITH AMAZON SAGEMAKER
SAGEMAKER WORKSHOP – BUILD, TRAIN AND DEPLOY ML MODELS AT SCALE WITH AMAZON SAGEMAKER
OCTOBER 8, 2018 | 9:30 A.M. – 12:30 P.M. ATKINSON HALL, QUALCOMM INSTITUTE, UC SAN DIEGO PLEASE REGISTER HERE
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:
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.
OCTOBER 8, 2018 | 9:30 A.M. – 12:30 P.M. ATKINSON HALL, QUALCOMM INSTITUTE, UC SAN DIEGO PLEASE REGISTER HERE
- Satellite imagery, MXNet, LandSat dataset : automatically mapping buildings in Vietnam
- Chemistry, DeepChem: building an online compound solubility prediction workflow
- Genomics, 1000 genomes dataset
- AWS
- Python
- Jupyter notebooks
- Basic machine learning methods
- AWS Account (already created)
- Access to SageMaker, S3, ECR from your IAM role.
- Access to SageMaker service role AmazonSageMaker-ExecutionRole or ability to create IAM roles.
Date and Time
Oct 8, 2018–Oct 8, 2018
from 9:30am–12:30pm
Location
Event Registration
Registration for this event is required
by .
Visit the registration page for details.
Event Fee
Free
Contact
Heather Matson • matsonh@amazon.com • 858-776-6913
Audience
Faculty, Staff, Students, The General Public
Event Host
AWS