Sep 23–26, 2019

Building a recommender system with Amazon ML Services

Karthik Sonti (Amazon Web Services), Emily Webber (Amazon Web Services), Varun Rao Bhamidimarri (Amazon Web Services)
1:30pm5:00pm Tuesday, September 24, 2019
Location: 1A 21/22
Secondary topics:  Cloud Platforms and SaaS, Deep dive into specific tools, platforms, or frameworks

Who is this presentation for?

Data scientists, machine learning engineers, and data engineers

Level

Intermediate

Description

In this workshop we’ll introduce the Amazon SageMaker machine learning platform, followed by a high level discussion of recommender systems. Next we’ll dig into different machine learning approaches for recommender systems. This will include common methods such as matrix factorization as well as newer embedding approaches. We’ll discuss the cold-start problem (recommending new products that don’t have purchase or review history) and approaches that can be used to address. Attendees will also learn how to label datasets using Amazon SageMaker Ground Truth, and build a recommendation engine that is highly customized to their preferences. Using built-in Amazon SageMaker Factorization Machines, BlazingText Word2Vec algorithm and Amazon Personalize, we will show how to train and then deploy them to a real-time, product-grade hosted endpoint. Finally, we’ll explore natural language generation techniques that can generate new text as product reviews.

Prerequisite knowledge

- Python and general understanding on recommender systems - A working knowledge of AWS (useful but not required)

Materials or downloads needed in advance

- Laptop

What you'll learn

Audience will walkway with understanding and working prototypes for building recommender systems using Amazon AI/ML services
Photo of Karthik Sonti

Karthik Sonti

Amazon Web Services

As a AWS Partner Solution Architect I work with GSI’s to help accelerate adoption of AWS services with a focus on Analytics and Machine learning

Photo of Emily Webber

Emily Webber

Amazon Web Services

As a ML Specialist Solutions Architect, i work with customers to educate them on various AWS machine learning services and platform offering

Varun Rao Bhamidimarri

Amazon Web Services

Enterprise Solution Architect helping customers with adoption of of cloud enabled analytics solutions to meet business requirements.

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