Machine learning and cognition in enterprises : business intelligence transformed /: business intelligence transformed. ([2017])
- Record Type:
- Book
- Title:
- Machine learning and cognition in enterprises : business intelligence transformed /: business intelligence transformed. ([2017])
- Main Title:
- Machine learning and cognition in enterprises : business intelligence transformed
- Further Information:
- Note: Rohit Kumar.
- Authors:
- Kumar, Rohit
- Contents:
- At a Glance; Contents; About the Author; About the Technical Reviewer; Acknowledgments; Introduction; Chapter 1: Journey of Business Intelligence; Business Intelligence; Why & How It Started; Going Ahead; By the 1980s; On Entering the 2000s; Initial Use Cases; Later Use Cases; Shifting Paradigm; Customer Relationship Management; Market Research Analysis; Loyalty Management; Product Release; Case Study; BI Before Paradigm Shift; BI With Paradigm Shift; Chapter 2: Why Cognitive and Machine Learning?; Artificial Intelligence (AI) and Machine Learning (ML). Why Artificial Intelligence and Machine Learning?Why Cognitive?; Chapter 3: Artificial Intelligenceâ#x80;#x94;Basics; Overview; Goals of Artificial Intelligence; Components of Artificial Intelligence; Learning; Supervised Learning; Unsupervised Learning; Reinforcement Learning; Sensing; Acting; Reasoning and Problem Solving; Interpreting Language; Planning; Why AI?; Approaches; Symbolic Approaches; Mixed Symbolic Approaches; Agent-Oriented and Distributive Approaches; Integrative Approaches; Tools; Logic Programming; Automated Reasoning; Search Algorithms; Artificial Neural Networks; Summary. Chapter 4: Machine Learningâ#x80;#x94;BasicsMachine Learning; Machine Learning Tasks; Classification; Clustering; Regression; Connected Key Concepts; Deep Learning; Genetic Algorithms; Decision Tree and Association Rule; Bayesian Network; Speech Recognition; Biosurveillance; Machine Learning vs. Statistics; Business Use Case Example;At a Glance; Contents; About the Author; About the Technical Reviewer; Acknowledgments; Introduction; Chapter 1: Journey of Business Intelligence; Business Intelligence; Why & How It Started; Going Ahead; By the 1980s; On Entering the 2000s; Initial Use Cases; Later Use Cases; Shifting Paradigm; Customer Relationship Management; Market Research Analysis; Loyalty Management; Product Release; Case Study; BI Before Paradigm Shift; BI With Paradigm Shift; Chapter 2: Why Cognitive and Machine Learning?; Artificial Intelligence (AI) and Machine Learning (ML). Why Artificial Intelligence and Machine Learning?Why Cognitive?; Chapter 3: Artificial Intelligenceâ#x80;#x94;Basics; Overview; Goals of Artificial Intelligence; Components of Artificial Intelligence; Learning; Supervised Learning; Unsupervised Learning; Reinforcement Learning; Sensing; Acting; Reasoning and Problem Solving; Interpreting Language; Planning; Why AI?; Approaches; Symbolic Approaches; Mixed Symbolic Approaches; Agent-Oriented and Distributive Approaches; Integrative Approaches; Tools; Logic Programming; Automated Reasoning; Search Algorithms; Artificial Neural Networks; Summary. Chapter 4: Machine Learningâ#x80;#x94;BasicsMachine Learning; Machine Learning Tasks; Classification; Clustering; Regression; Connected Key Concepts; Deep Learning; Genetic Algorithms; Decision Tree and Association Rule; Bayesian Network; Speech Recognition; Biosurveillance; Machine Learning vs. Statistics; Business Use Case Example; Chapter 5: Natural Language Processing; Natural Language; Natural Language Processingâ#x80;#x94;Overview; NLP and Machine Learning; How NLP Works; Words and Letters First; Sentences Come After; Pragmatics; Business Cases; Chatbots; Spam Filters; Sentiment Analysis. Search EnginesQuestion Answering; Summary; Chapter 6: Predictive Analytics; Overview; Data Relevancy; Fresh and Genuine; Avoid Noise; Avoid Personal or Sensitive Data; Data Retention Period; Past, Current, and Future Value; Consistent and Not a Liability; Outdated or Out of Purpose; Predictive Analyticsâ#x80;#x94;Process; Sources and Storage; Data Modeling; Analytics; Reporting; Types of Analytics; Descriptive Analytics; Diagnostic Analytics; Prescriptive Analytics; Tools; SAP HANA Predictive Analytics; Apache Mahout; IBM SPSS; SAS; Statistical; Oracle Advanced Analytics; Actuate; Mathematica. Some ApplicationsManufacturing; Marketing and Demand Management; Predictive Maintenance; Flexi Pricing; Weather Forecast; Epidemic Management; R Chapter 7: Cognitive Computing; Cognition; Cognitive Computing; Cognitive Era; Cognitive Architecture; Soar; ACT-R; CMAC; CLARION; Cognitive Chip; Why Cognitive?; Was Always Desired; Big Data and Insights; Advisory; IoT Leverage; Business Continuity; Utilize Resources; Efficiency; Customer Satisfaction; Customized Care; More Ad Hoc; Generate Whatâ#x80;#x99;s Required; Look Inside; Cognitive + IoT; Use Cases; Cybersecurity; Oil and Gas; Healthcare. … (more)
- Publisher Details:
- Berkeley, CA : Apress
- Publication Date:
- 2017
- Copyright Date:
- 2017
- Extent:
- 1 online resource (xxviii, 306 pages)
- Subjects:
- 006.3/1
004
Computer science
Machine learning
COMPUTERS -- Computer Literacy
COMPUTERS -- Computer Science
COMPUTERS -- Data Processing
COMPUTERS -- Hardware -- General
COMPUTERS -- Information Technology
COMPUTERS -- Machine Theory
COMPUTERS -- Reference
Machine learning
Computers -- Software Development & Engineering -- General
Computers -- Programming -- Algorithms
Business & Economics -- Information Management
Computers -- Enterprise Applications -- General
Software Engineering
Algorithms & data structures
Business mathematics & systems
Artificial intelligence
Software engineering
Computer software
Management information systems
Computers -- Intelligence (AI) & Semantics
Artificial intelligence
Electronic books - Languages:
- English
- ISBNs:
- 9781484230695
1484230698
9781484230688 - Related ISBNs:
- 9781484230688
148423068X
148423068X - Notes:
- Note: Description based on online resource; title from digital title page (viewed on June 15, 2018).
- Access Rights:
- Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
- Access Usage:
- Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD.DS.353583
- Ingest File:
- 01_312.xml