Build an AI Application with React and AWS SageMaker
1h 12mIntermediate2024-04-19
Authors
Emmanuel Henri
Executive with 20+ years of experience in programming and design
Course details
When you want a lot more control over your data, but don't want to manage machine learning tools locally, AWS SageMaker can provide the bridge you need. In this course, Emmanuel Henri shows you how to train SageMaker on your data, tune the results, and then connect it to a React-based application for delivery to your users. Emmanuel takes you through the process step by step, from the initial setup of the project, to feature engineering, training and deployment, and working with the React front end.
Learning objectives
Load data into SageMaker.
Test and tune results from SageMaker.
Connect React component to SageMaker.
Integrate SageMaker and S3.
Learning objectives
Load data into SageMaker.
Test and tune results from SageMaker.
Connect React component to SageMaker.
Integrate SageMaker and S3.
Skills covered
Amazon SageMakerReact.jsMetaCloud DevelopmentFront-End Web DevelopmentArtificial Intelligence FoundationsCloud ServicesArtificial Intelligence (AI)Web DevelopmentCloud ComputingOne-Off
Concepts
0. Introduction
- 01 - Build an AI application with React and SageMaker
- 02 - Course prerequisites
1. Introduction and Setup
- 03 - Basics of machine learning
- 04 - Introduction to SageMaker
- 05 - AWS SageMaker setup
- 06 - Initializing the React project
2. Feature Engineering
- 07 - Introduction to SageMaker Data Wrangler
- 08 - Data cleaning and processing with Data Wrangler
- 09 - Feature engineering and transforming data
3. Training and Deployment
- 10 - Overview of algorithms and the training process
- 11 - Train the model with Autopilot
- 12 - Review models and deploy
- 13 - Predict and clean up resources
4. React Front End
- 14 - Base app component
- 15 - Form component
- 16 - Results component
- 17 - Finish results component
Conclusion
- 18 - Continue learning SageMaker