Linkedin - Build an AI Application with React and AWS SageMaker
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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
| 1. Introduction/1. Build an AI application with React and SageMaker.mp4 | 4.02 MiB |
| 1. Introduction/2. Course prerequisites.mp4 | 919.32 KiB |
| 2. Introduction and Setup/1. Basics of machine learning.mp4 | 2.57 MiB |
| 2. Introduction and Setup/2. Introduction to SageMaker.mp4 | 2.99 MiB |
| 2. Introduction and Setup/3. AWS SageMaker setup.mp4 | 4.31 MiB |
| 2. Introduction and Setup/4. Initializing the React project.mp4 | 4.91 MiB |
| 3. Feature Engineering/1. Introduction to SageMaker Data Wrangler.mp4 | 17.1 MiB |
| 3. Feature Engineering/2. Data cleaning and processing with Data Wrangler.mp4 | 13.56 MiB |
| 3. Feature Engineering/3. Feature engineering and transforming data.mp4 | 16.38 MiB |
| 4. Training and Deployment/1. Overview of algorithms and the training process.mp4 | 6.66 MiB |
| 4. Training and Deployment/2. Train the model with Autopilot.mp4 | 9.68 MiB |
| 4. Training and Deployment/3. Review models and deploy.mp4 | 11.08 MiB |
| 4. Training and Deployment/4. Predict and clean up resources.mp4 | 4.26 MiB |
| 5. React Front End/1. Base app component.mp4 | 11.98 MiB |
| 5. React Front End/2. Form component.mp4 | 13.51 MiB |
| 5. React Front End/3. Results component.mp4 | 16.89 MiB |
| 5. React Front End/4. Finish results component.mp4 | 25.15 MiB |
| 6. Conclusion/1. Continue learning SageMaker.mp4 | 1.09 MiB |
| Ex_Files_AI_App_React_AWS_SageMaker.zip | 20.38 MiB |
