Machine Learning in the AWS Cloud
Add Intelligence to Applications with Amazon SageMaker and Amazon Rekognition
Created by Abhishek Mishra
Explore how to build intelligent applications using machine learning and AWS services. You will start with the basics of data preparation and model evaluation, then move on to hands-on experience with Amazon SageMaker, Rekognition, and other AWS tools. By the end, you will know how to integrate machine learning into real-world cloud applications.
Wiley | Sep 2026 | 528 min
What You Will Learn
You will begin by learning the foundations of machine learning and data handling in Python. Step by step, you will explore AWS services like S3, Lambda, and SageMaker through practical examples. Each section builds on the last, guiding you from data preparation to deploying and integrating AI features into cloud-based applications.
Key Features
- Understand and apply core machine learning concepts using AWS services
- Prepare, visualize, and evaluate data for predictive modeling in Python
- Deploy, manage, and scale intelligent features with SageMaker and Rekognition
Target Audience
Ideal for developers, data scientists, and cloud professionals with basic Python and data skills. If you want to add machine learning capabilities to your AWS projects or bring intelligence to your applications, you will find clear guidance and practical workflows to help you achieve your goals.
