Book Image

Machine Learning with AWS

By : Jeffrey Jackovich, Ruze Richards
Book Image

Machine Learning with AWS

By: Jeffrey Jackovich, Ruze Richards

Overview of this book

<p>Machine Learning with AWS is the right place to start if you are a beginner interested in learning useful artificial intelligence (AI) and machine learning skills using Amazon Web Services (AWS), the most popular and powerful cloud platform. You will learn how to use AWS to transform your projects into apps that work at high speed and are highly scalable. From natural language processing (NLP) applications, such as language translation and understanding news articles and other text sources, to creating chatbots with both voice and text interfaces, you will learn all that there is to know about using AWS to your advantage. You will also understand how to process huge numbers of images fast and create machine learning models.</p> <p>By the end of this book, you will have developed the skills you need to efficiently use AWS in your machine learning and artificial intelligence projects.</p>
Table of Contents (9 chapters)
Machine Learning with AWS
Preface

Summary


In this chapter, you learned how to use the various features of the Amazon Rekognition service and applied this to images. First, you used the service to recognize objects and scenes in images. Next, you moderated images that might have objectionable content by using Rekognition to recognize the objectionable content in the images.

You were able to analyze faces with Rekognition and were also able to identify their gender, age range, whether they were smiling, and whether they were wearing glasses.

You also recognized celebrities and famous people with the service, and compared faces in different images to see whether they were the same. Finally, you were able to extract text that was displayed in images.

These types of features would have seemed unbelievable just a few years ago. The nature of machine learning and artificial intelligence is that immense strides have been made recently, today, and into the foreseeable future in terms of what computers are going to be able to do — and...