Machine Learning with AWS

Description

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. 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. Preface......Page 9 Introduction to Amazon Web Services......Page 15 What is Artificial Intelligence?......Page 16 What is Amazon S3?......Page 17 AWS Free-Tier Account......Page 18 Core S3 Concepts......Page 19 S3 Operations......Page 21 REST Interface......Page 22 Exercise 1: Using the AWS Management Console to Create an S3 Bucket......Page 23 Exercise 2: Importing and Exporting the File with your S3 Bucket......Page 26 Exercise 3: Configuring the Command-Line Interface......Page 31 Recursion and Parameters......Page 36 Activity 1: Importing and Exporting the Data into S3 with the CLI......Page 37 Exercise 4: Navigating the AWS Management Console......Page 38 Activity 2: Testing the Amazon Comprehend's API Features......Page 40 Summary......Page 41 SummarizingText Documents Using NLP......Page 43 What is Natural Language Processing?......Page 44 Using Amazon Comprehend to Inspect Text and Determine the Primary Language......Page 45 Exercise 5: Detecting the Dominant Language Using the Command-Line Interface in a text document......Page 46 Exercise 6: Detecting the Dominant Language in Multiple Documents by Using the Command-Line Interface (CLI)......Page 49 Detecting Named Entities – AWS SDK for Python (boto3)......Page 50 Exercise 7: Determining the Named Entities in a Document......Page 52 DetectEntities in a Set of Documents (Text Files)......Page 54 Exercise 8: Determining the Key Phrase Detection.......Page 55 Exercise 9: Detecting Sentiment Analysis......Page 56 What is AWS Lambda?......Page 58 Lambda Function Anatomy......Page 59 Exercise 10: Setting up a Lambda function for S3......Page 60 Exercise 11: Configuring the Trigger for an S3 Bucket......Page 66 Exercise 12: Assigning Policies to S3_trigger to Access Comprehend......Page 70 Activity 3: Integrating Lambda with Amazon Comprehend to Perform Text Analysis......Page 72 Summary......Page 74 Perform Topic Modeling and Theme Extraction......Page 77 Topic Modeling with Latent Dirichlet Allocation (LDA)......Page 78 Why Use LDA?......Page 79 Amazon Comprehend–Topic Modeling Guidelines......Page 80 Exercise 13: Topic Modeling of a Known Topic Structure......Page 82 Exercise 14: Performing Known Structure Analysis......Page 98 Activity 4: Perform Topic Modeling on a Set of Documents with Unknown Topics......Page 101 Summary......Page 102 Creating a Chatbot with Natural Language......Page 105 The Business Case for Chatbots......Page 106 Core Concepts in a Nutshell......Page 107 Introduction......Page 110 Exercise 15: Creating a Sample Chatbot to Order Flowers......Page 111 Creating a Custom Chatbot......Page 119 A Bot Recognizing an Intent and Filling a Slot......Page 121 Exercise 16: Creating a Bot that will Recognize an Intent and Fill a Slot......Page 122 Natural Language Understanding Engine......Page 132 Lambda Function – Implementation of Business Logic......Page 134 Exercise 17: Creating a Lambda Function to Handle Chatbot Fulfillment......Page 135 Implementing the Lambda Function......Page 137 Input Parameter Structure......Page 138 Implementing the Function to Retrieve the Market Quote......Page 139 Returning the Information to the Calling App (The Chatbot)......Page 140 Connecting to the Chatbot......Page 141 Summary......Page 143 Using Speech with the Chatbot......Page 145 Free Tier Information......Page 146 Interacting with the Chatbot......Page 147 Talking to Your Chatbot through a Call Center using Amazon Connect......Page 148 Exercise 18: Creating a Personal Call Center......Page 149 Exercise 19: Obtaining a Free Phone Number for your Call Center......Page 155 Using Amazon Lex Chatbots with Amazon Connect......Page 157 Contact Flow Templates......Page 158 Exercise 20: Connect the Call Center to Your Lex Chatbot......Page 159 Activity 1: Creating a Custom Bot and Connecting the Bot with Amazon Connect......Page 168 Summary......Page 169 Analyzing Images with Computer Vision......Page 171 Amazon Rekognition Basics......Page 172 Rekognition and Deep Learning......Page 173 Detect Objects and Scenes in Images......Page 174 Exercise 21: Detecting Objects and Scenes using your own images......Page 177 Image Moderation......Page 180 Exercise 22: Detecting objectionable content in images......Page 183 Facial Analysis......Page 185 Exercise 23: Analyzing Faces in your Own Images......Page 186 Celebrity Recognition......Page 191 Exercise 24: Recognizing Celebrities in your Own Images......Page 193 Face Comparison......Page 196 Activity 1: Creating and Analyzing Different Faces in Rekognition......Page 198 Text in Images......Page 199 Exercise 25: Extracting Text from your Own Images......Page 200 Summary......Page 203 Appendix A......Page 205 Index......Page 249 _GoBack......Page 236