book

Getting Started with Artificial Intelligence, 2nd Edition

by Tom Markiewicz, Josh Zheng

October 2020

Beginner

83 pages

1h 55m

English

O'Reilly Media, Inc.

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The Market for Artificial IntelligenceAvoiding an AI WinterArtificial Intelligence, Defined?Artificial IntelligenceMachine LearningDeep LearningApplications in the EnterpriseNext Steps
Overview of NLPThe Components of NLPEntitiesRelationsConceptsKeywordsSemantic RolesCategoriesEmotionSentimentEnterprise Applications of NLPSocial Media AnalysisCustomer SupportBusiness IntelligenceContent Marketing and RecommendationAdditional TopicsHow to Use NLPTraining ModelsChallenges of NLPSummary
What Is a Chatbot?The Rise of ChatbotsNatural Language Processing in the CloudProliferation of Messaging PlatformsNatural Language InterfaceHow to Build a ChatbotThe Messaging ChannelThe BackendChallenges of Building a Successful ChatbotSummary
Capabilities of Computer Vision for the EnterpriseImage Classification and TaggingObject LocalizationCustom ClassifiersHow to Use Computer VisionComputer Vision on Mobile DevicesBest PracticesQuality Training ImagesUse CasesSatellite ImagingVideo Search in Surveillance and EntertainmentAdditional Examples: Social Media and InsuranceExisting Challenges in Computer VisionImplementing a Computer Vision SolutionSummary
Preparing for a Data PipelineSourcing Big DataStorage: Apache HadoopHadoop as a Data LakeDiscovery: Apache SparkSpark Versus MapReduceMachine Learning with SparkAutomationWhy Automated AI/ML?Limitations of AutoMLExisting Automated Machine Learning SolutionsSummary
Overview of CloudsConcerns about the CloudPublic and PrivateHybridMulticloudCloud ConstructionUsing AI on Hybrid CloudsPrivacy and SecurityPortability and ScalabilityProcessing and Computing PowerExample of AI on Hybrid CloudsPractical SolutionsThe Future of AI on Hybrid CloudsSummary
What Makes Enterprises Unique?Current Challenges, Trends, and OpportunitiesLittle DataInaccessible Data FormatsEnsuring Accountability and InterpretabilityFairness, Trust, and TransparencyScalabilitySocial ImplicationsSummary

Overview

Getting started in enterprise AI can be daunting. Is your data pipeline robust enough? Do you want to mine unstructured data in emails, blog posts, and other documents? Build a chatbot? Use computer vision to classify images? Where do you start? And how do you make sure your first attempts succeed?

This book is the ideal starting point for your journey into enterprise AI. Through case studies, implementation examples, and a survey of the landscape, developers will learn technologies for automating and detecting patterns that can augment human expertise and empower employees and applications to make rich, data-driven decisions.

In the second edition, authors Tom Markiewicz and Josh Zheng--developer advocates for IBM--examine common use cases for AI in the enterprise, including natural language processing (NLP) and computer vision. You'll also explore a new chapter on hybrid and private clouds.

Get a complete introduction to artificial intelligence and survey the growing AI market
Explore a high-level guide to data pipelines and hybrid clouds--the backbone of your AI applications
Learn why NLP is the key to mining unstructured data in emails, articles, blog posts, customer support discussions, and other documents
Examine capabilities that computer vision brings to your applications, including image classification and tagging

AI integration is fast becoming a fundamental component of business growth across a wide range of industries. With this book, your company will learn how to take advantage of this unique technology.