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Machine learning with AWS : explore the power of cloud services for your machine learning and artificial intelligence projects /
In this book, you will learn about the various artificial intelligence and machine learning services available on AWS. Through practical hands-on exercises, you'll learn how to use these services to generate impressive results. By the end of this book, you will have a basic understanding of how...
| Clasificación: | Libro Electrónico |
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| Autor principal: | |
| Otros Autores: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Birmingham :
Packt Publishing Ltd,
2018.
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| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- Intro; Preface; Introduction to Amazon Web Services; Introduction; What is AWS?; What is Machine Learning?; What is Artificial Intelligence?; What is Amazon S3?; Why use S3?; The Basics of Working on AWS with S3; AWS Free-Tier Account; Importing and Exporting Data into S3; How S3 Differs from a Filesystem; Core S3 Concepts; S3 Operations; Data Replication; REST Interface; Exercise 1: Using the AWS Management Console to Create an S3 Bucket; Exercise 2: Importing and Exporting the File with your S3 Bucket; AWS Command-Line Interface (CLI); Exercise 3: Configuring the Command-Line Interface.
- Command Line-Interface (CLI) UsageRecursion and Parameters; Activity 1: Importing and Exporting the Data into S3 with the CLI; Using the AWS Console to Identify Machine Learning Services; Exercise 4: Navigating the AWS Management Console; Activity 2: Testing the Amazon Comprehend's API Features; Summary; SummarizingText Documents Using NLP; Introduction; What is Natural Language Processing?; Using Amazon Comprehend to Inspect Text and Determine the Primary Language; Exercise 5: Detecting the Dominant Language Using the Command-Line Interface in a text document.
- Exercise 6: Detecting the Dominant Language in Multiple Documents by Using the Command-Line Interface (CLI)Extracting Information in a Set of Documents; Detecting Named Entities
- AWS SDK for Python (boto3); DetectEntites
- Input and Output; Exercise 7: Determining the Named Entities in a Document; DetectEntities in a Set of Documents (Text Files); Detecting Key Phrases; Exercise 8: Determining the Key Phrase Detection.; Detecting Sentiments; Exercise 9: Detecting Sentiment Analysis; Setting up a Lambda function and Analyzing Imported Text Using Comprehend; What is AWS Lambda?
- What does AWS Lambda do?Lambda Function Anatomy; Exercise 10: Setting up a Lambda function for S3; Exercise 11: Configuring the Trigger for an S3 Bucket; Exercise 12: Assigning Policies to S3_trigger to Access Comprehend; Activity 3: Integrating Lambda with Amazon Comprehend to Perform Text Analysis; Summary; Perform Topic Modeling and Theme Extraction; Introduction; Extracting and Analyzing Common Themes; Topic Modeling with Latent Dirichlet Allocation (LDA); Basic LDA example; Why Use LDA?; Amazon Comprehend-Topic Modeling Guidelines; Exercise 13: Topic Modeling of a Known Topic Structure.
- Exercise 14: Performing Known Structure AnalysisActivity 4: Perform Topic Modeling on a Set of Documents with Unknown Topics; Summary; Creating a Chatbot with Natural Language; Introduction; What is a Chatbot?; The Business Case for Chatbots; What is Natural Language Understanding?; Core Concepts in a Nutshell; Setting Up with Amazon Lex; Introduction; Exercise 15: Creating a Sample Chatbot to Order Flowers; Creating a Custom Chatbot; A Bot Recognizing an Intent and Filling a Slot; Exercise 16: Creating a Bot that will Recognize an Intent and Fill a Slot; Natural Language Understanding Engine.
- Lambda Function
- Implementation of Business Logic.