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

Using the AWS Console to Identify Machine Learning Services


The AWS Console provides a web-based interface to navigate, discover, and utilize AWS services for AI and ML. In this topic, we will explore two ways to use the Console to search Machine Learning services. In addition, we will test an ML API with text data retrieved from a website.

Exercise 4: Navigating the AWS Management Console

In this exercise, we will navigate the AWS Management Console to locate Machine Learning services. Starting from the console https://console.aws.amazon.com/console/ and only using console search features, navigate to the Amazon Lex https://console.aws.amazon.com/lex/ service information page:

  1. Click on https://console.aws.amazon.com/console/ to navigate to the AWS Console. Then, click on Services:

    Figure 1.31: AWS Console

  2. Scroll down the page to view all of the Machine Learning services. Then, click on Amazon Lex:

    Figure 1.32: Options for Machine Learning

  3. You will be redirected to the Amazon Lex home screen:

    Figure 1.33: Amazon Lex home screen

Locating new AWS Services is an essential skill for discovering more tools to provide solutions for your data projects. Now, let's review another way to locate Machine Learning resources via the Search bar.

Activity 2: Testing the Amazon Comprehend's API Features

In this activity, we will display text analysis output by using a partial text file input in the API explorer. Exploring an API is a skill that saves development time by making sure that the output is in a desired format for your project. Thus, we will test Comprehend's text analysis features.

Suppose that you are an entrepreneur creating a chatbot. You have identified a business topic and the corresponding text documents, with content that will allow the chatbot to make your business successful. Your next step is to identify/verify an AWS service to parse the text document for sentiment, language, key phrases, and entities. Before investing time in writing a complete program, you want to test the AWS service's features via the AWS Management Console's interface. To ensure that this happens correctly, you will need to search the web for an article (written in English or Spanish) that contains the subject matter (sports, movies, current events, and so on) that you're interested in. The AWS Management Console is also accessible via the root user's account.

You are aware that exploring APIs is a skill that can save development time by ensuring that the output is in a desired format for your project. The following are the steps of completion:

  1. Identify an AWS service, via the AWS Management Console, to accomplish your objectives.

  2. Navigate to your web page of choice, which contains articles in English and Spanish.

  3. Copy the text from the article written in English or Spanish, in order to identify the following features: sentiment, language, key phrases, and entities.

  4. Obtain a score representing the articles: sentiment, language, key phrases, and entities.

Note

To refer to the detailed steps, go to the Appendix A at the end of this book on Page no. 194