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Sep 4-5, 2018: Training
Sep 5-7, 2018: Tutorials & Conference
San Francisco, CA

Building deep learning applications with Amazon SageMaker

David Arpin (Amazon Web Services)
1:30pm-5:00pm Wednesday, September 5, 2018
Models and Methods
 Location: Continental 4
Secondary topics:  Deep Learning tools
Average rating: ****.
(4.00, 2 ratings)

Who is this presentation for?

  • Data scientists and machine learning scientists and engineers

Prerequisite knowledge

  • A basic understanding of Python, deep learning (i.e., what is a neural network and how are they trained), and TensorFlow or a similar deep learning framework

Materials or downloads needed in advance

  • A laptop with access to AWS (You'll be provided a temporary account but are free to use your own.)
  • A GitHub account

What you'll learn

  • Learn how to use Amazon SageMaker to build, train, and deploy deep learning models

Description

David Arpin offers an overview of the Amazon SageMaker machine learning platform, walking you through setup and using Amazon SageMaker Notebook (a hosted Jupyter Notebook server). You’ll get hands-on experience with SageMaker’s built-in deep learning algorithm as you dive into building your own neural network architecture using SageMaker’s prebuilt TensorFlow containers.

Outline:

  • Overview of the Amazon SageMaker machine learning platform
  • Setup and Amazon SageMaker Notebook (a hosted Jupyter Notebook server)
  • Hands-on training using a built-in SageMaker deep learning algorithm
  • Building your own neural network architecture using SageMaker’s prebuilt TensorFlow containers
Photo of David Arpin

David Arpin

Amazon Web Services

David Arpin is a product manager and data scientist at AWS. He works closely with the teams that develop built-in algorithms and deep learning frameworks for Amazon SageMaker. He also actively contributes to, and helps maintain, the SageMaker examples GitHub repository (https://github.com/awslabs/amazon-sagemaker-examples). Prior to that he led a data science team in Fulfillment By Amazon, and worked at two beer companies, and a large grocery retailer.