Cognitive Computing with IBM Watson电子书

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Preface

Who this book is for

What this book covers

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Background, Transition, and the Future of Computing

Transitioning from conventional to cognitive computing

Limitations of conventional computing

Solving conventional computing's problems

Workings of machine learning

Machine learning and its uses

Cons of machine learning

Introduction to IBM Watson

Hardware and software requirements

Signing up for IBM Cloud

Summary

Can Machines Converse Like Humans?

Creating a conversational agent workspace

Creating an instance of Watson Assistant and a workspace

The sample application

Creating a set of conversational intents

Recognizing entities

Identifying entities through annotators

Building a dialog

Creating the dialog for a complex Intent using Frame Slots

Context variables

Programming your conversation application

Emerging features

Summary

Further reading

Computer Vision

Can machines visually perceive the world around them?

The past – classical computer vision

The present – deep learning for computer vision

Creating a basic image-recognition system

Creating an instance of Watson Visual Recognition and a classifier

Uploading data and training the classifier

Testing the classifier

Creating a Python application to classify with Watson

Handling the case where you don't have training data

Using the facial detection model

Summary

This Is How Computers Speak

A computer that talks

Playing sound through the speaker

Getting fancier with how to speak

Controlling pronunciation

Customizing speech synthesis

Using sounds-like customization

Streaming and timing

A fun application of the speech service

Talking to the computer

Getting voice from a microphone

Using the WebSockets interface to speech recognition

Telephones are not good microphones

More about base models

Dealing with speaker hesitations

Customizing the speech recognition service

Customizing Watson's language model

Customizing the acoustic model for Watson

Leveraging batch processing

Summary

Further reading

Expecting Empathy from Dumb Computers

Introducing empathy

Understanding the complexities of sentiment

The functionality of the Tone Analyzer API

How you can use the Tone Analyzer API

Understanding personality through natural language

Using natural language to infer personality traits

Calling the Personality Insights API

Summary

Language - How Watson Deals with NL

Natural language translation – the past

Natural language – it's intrinsically unstructured

Natural language translation – the present

Translating between languages with Language Translator

Training custom NMT models with Watson

Categorizing text using Natural Language Classifier

Summary

Further reading

Structuring Unstructured Content Through Watson

Using computers that recognize what you mean

Introducing the NLU service

Alternative sources of literature

Types of analyses

Categories

Concepts

Emotion

Sentiment

Entities

Relations

Keywords

Semantic roles

Parts of speech (syntax)

Customizing NLU

Preparing to annotate

Creating a type system

Adding documents

As an aside

Preparing documents for use in Watson Knowledge Studio

Loading documents into Watson Studio

Performing annotations

Editing the type system

The importance of being thorough

Coreferences

Training Watson

Deploying the custom model to NLU

Using a custom model in NLU

Summary

Putting It All Together with Watson

Recapping Watson Services

Building a sample application from Watson Services

The use case and application

The program flow

Translating voice input

Determining intent

Prompting the user for their input

Setting the document of interest

Summarizing entities and concepts

Identifying an entity of interest

Assessing the personality of the entity

Assessing the tone of the entity

Translating text

Classifying text

Running the program

Setup

Summary

Future - Cognitive Computing and You

Other services and features of Watson

Compare and Comply

Discovery

Watson Studio

Machine learning

Knowledge catalog

Watson OpenScale

The future of Watson

Advances in AI

Generative adversarial networks

Conversational systems

Deep learning

Edge computing

Bias and ethics in AI

Robotics and embodiment

Quantum computing and AI

The future of AI

Summary

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