Create real-time, personalized movie recommendations with Amazon Personalize

Introduction

Introduction

Module 1

Background and setup

Module 2

Download and prepare dataset

Module 3

Import dataset

Module 4

Create solution

Module 5

Create campaign and get recommendations

Clean up

Clean up and next steps

Introduction

In this lab, you learn how to how to create real-time personalized movie recommendations with Amazon Personalize.

Amazon Personalize is a fully managed machine learning service that enables developers to build customized recommendation systems. Amazon Personalize makes it easy for developers to build applications capable of delivering a wide range of personalization experiences, including specific product recommendations, personalized product re-ranking, and customized direct marketing.
 
This lab walks you through the steps to create a personalized movie recommendation system, you can use these same steps to create other personalize content recommendations such as music or audio books.

Why use Amazon Personalize for a recommendation system?

Amazon Personalize does not require machine learning experience. You can build, train, and deploy a Amazon Personalize recommendation model (a solution version) with the AWS Management Console or programmatically by using the AWS SDK for Python. As a developer, you only need to do the following:

  • Format input data and upload the data into an Amazon S3 bucket, or send real-time event data.
  • Select a training recipe (algorithm) to use on the data.
  • Train a model (called a solution version in Amazon Personalize) using the recipe.
  • Deploy a campaign to make real-time recommendations or a batch processing job for batch recommendations.

Requirements

AWS Experience: Intermediate

Time to complete: 2 hours

Cost to complete: This tutorial will cost you less than $1 (assuming all services are running for 2 hours)*

Technologies used:

• Active AWS Account**
• Browser: AWS recommends Chrome
• Amazon Personalize
• Amazon SageMaker
• AWS Identity and Access Management
• Amazon S3
• AWS SDK for Python

*This estimate assumes you follow the recommended configurations throughout the tutorial and terminate all resources within 2 hours.

**Accounts that have been created within the last 24 hours might not yet have access to the resources required for this project.

Start Module 1: Background and setup