1Chapter 1. Data Science
839.5 Bottom-Up Approach
2Abstract
849.6 Various Industries use Data and AI
31.1 Analyzing the Data Science
859.7 Benefits from Statistics
41.2 Lifecycle of Data Science
869.9 Summary
51.3 Tools For Data Science
879.10 Inquiries
61.4 Types Of Data Science Work
88Chapter 10. Long Term Availability
71.5 Components of Data Science
89Abstract
81.6 Machine Learning in Data Science
9010.1 Avoid Hard Coding
91.7 Data science and IBM Cloud
9110.2 Overloading
101.8 Application of Data Science
9210.3 Locked In
111.9 Summary
9310.4 Ownership and Decomposition
121.10 Inquiries
9410.5 Avoiding Changing in Design
13Chapter 2. Stepping into AI
9510.6 Summary
14Abstract
9610.7 Inquiries
152.1 Building base data for AI
97Chapter 11. Extending Value Data Through AI
162.3 Choosing the Ladder rung by rung
98Abstract
172.4 Adapting to Retain Organizational
9911.1 Emphasizing the AI
18Relevance
10011.2 Polyglot Persistence
192.5 Data-Based in Modern Business
10111.3 Profit in Data Literacy
202.6 Developing AI-centric organization
10211.4 Skill Sets
212.7 Summary
10311.5 Pursuing AI
222.8 Inquiries
10411.6 Creating Metadata
23Chapter 3. Data Science Organization Using AI
10511.7 Right Movement to Data
24Abstract
10611.8 Summary
253.1 Artificial Intelligence cooperating with
10711.9 Inquiries
26data analytics
108Chapter 12. An IA for AI
273.2 Decision making in AI
109Abstract
283.3 Standardizing data and data science
11012.1 Development Effort for AI
293.4 Data science for the enterprise
11112.2 Machine Learning Model
303.5 Facilitating data in a reaction time
11212.3 Data Drift
313.6 Summary
11312.4 Essential elements
323.7 Inquiries
11412.6 Intersections
33Chapter 4. Working With Data And AI
11512.7 Interoperability Across Element
34Abstract
11612.8 Driving Action
354.1 User-friendly data
11712.9 Keep It Simple
364.2 Data governance
11812.10 Organizing Data zones
374.2 Data Governance
11912.11 Possibilities of Open Platforms
384.3 Encapsulation Knowledge
12012.12 Summary
394.4 Summary
12112.13 Inquiries
404.5 Inquiries
122Chapter 13. Data Governance for Creating Trust in Data Science Decision Outcomes
41Chapter 5. Smarter Learning Software
123Abstract
42Abstract
12413.1 Transformation of business
435.1 Preaching big data imaginary
12513.2 Data Science Decision-Making Outcomes
445.2 Powerful data and algorithms
12613.2 The Role of Data Governance with Regards
455.3 New normal is big data
127to Data Science as a Product of Human Agency
465.4 Data Management for AI
12813.3 The Role of Data Governance with Regards
475.5 Summary
129to Data Science as a Medium of Human Agency
485.6 Inquiries
13013.4 The Role of Data Governance with Regards
49Chapter 6. Looking Forward to Analytics
131to Organizational Conditions of Interaction
50Abstract
132with Data Science
516.1 Need for Organization
13313.5 The Role of Data Governance with Regards
526.1.2 The raw zone
134to the Organizational Consequences of Data
536.2 Data Topologies
135Science
546.3 Exploring Various Zones
13613.7 Summary
556.4 Summary
13713.8 Inquiries
566.5 Inquiries
138Chapter 14. Big Data Analytics Creates Business Value in Smart Manufacturing
57Chapter 7. Optimizing Disciplines on AI Ladder
139Abstract
58Abstract
14014.1 Cyber-Physical System
597.1 Operational AI
14114.2 Big Data Analytics in Smart Manufacturing
607.2 Time Passage
14214.3 Business value of IT frameworks
617.3 Create
14314.4 Science and Technology in Industry
627.4 Execute
14414.5 Computing Devices and Internet
637.5 Operating the work
14514.6 Context-aware Mobile computing
647.6 Business-driven tools for Software
14614.8 Mobile systems and services
65Industry
14714.7 Summary
667.7 Summary
14814.8 Inquiries
677.8 Inquiries
149Chapter 15. Modernization of Data Science in AI
68Chapter 8. Value Edition and Maximizing the Use of Data
150Abstract
69Abstract
15115.1 Case Study
708.1 Marching Towards Value Chain
15215.2 Biomedical Engineer’s Station
718.2 Curation
15315.3 AI in Media Platforms
728.3 Socializing the Data
15415.4 IBM Commercial Process
738.4 Integrated Data Management
15515.5 Hadoop Ecosystem
748.5 Multi-Tenacy
15615.6 Image and Speech Recognition
758.6 Summary
15715.7 Investing and Financing
768.7 Inquiries
15815.8 Manufacturers using IoT
77Chapter 9. Statistical Analysis For Valuing Data
15915.9 Telephonic Communication
78Abstract
16015.10 Summary
799.1 Data Management Through Asset
16115.11 Inquiries
809.2 Inexact Science
162Glossary
819.3 Data Inequality Among Users
163Index
829.4 Accessing the Data in Control
