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

Content preview from Getting Started with Artificial Intelligence, 2nd Edition

Chapter 1. Introduction to Artificial Intelligence

In the future, AI will be diffused into every aspect of the economy.

Nils J. Nilsson, founding researcher, Artificial Intelligence & Computer Science, Stanford University

Beyond the buzzwords, media coverage, and hype, artificial intelligence techniques are becoming a fundamental business growth component across a wide range of industries. And while the various terms (algorithms, transfer learning, deep learning, neural networks, NLP, etc.) associated with AI are thrown around in meetings and product planning sessions, it’s easy to be skeptical of the potential impact of these technologies.

Today’s media represents AI in many ways, both good and bad—from the fear of machines taking over all human jobs and portrayals of evil AIs via Hollywood to the much-lauded potential of curing cancer and making our lives easier. Of course, the truth is somewhere in between.

While there are valid concerns about how the future of artificial intelligence will play out (and the social implications), the reality is that the technology is currently used in companies across all industries.

AI is used everywhere—IoT (Internet of Things) and home devices, commercial and industrial robots, autonomous vehicles, drones, digital assistants, and even wearables. And that’s just the start. AI will drive future user experiences that are immersive, continuous, ambient, and conversational. These conversational services (e.g., chatbots and virtual agents) are ...