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Home » ICT » ICT Services » IIC-8641217
  • Global Machine Learning Market Research Reports Insights, Opportunity, Analysis, Market Shares And Forecast 2017 – 2023

  • Publish: December 2017 | Report Code: IIC-8641217

* For discount/customization and buying a particular chapter click here or write to us at sales@occamsresearch.com

Machine learning is an application of artificial intelligence (AI) technology which provide abilityto automatically learn as well as improve from experience without being explicitly programmedto the system. Machine learning platform majorly focuses on development ofcomputer programs which can access data and further use it to learn for themselves (self learning).The global machine learning market is expected to rise with the CAGR of about 44% during forecast period 2016-2023. Machine learning has the ability to process large amount of data easily with timely analysis as well as assessment. Also, machine learning algorithms tend to operate at expedited levels by providing fast processing and real-time predictions, which promotes growth of global machine learning market during forecast period.

Proliferation in data generation is one of the major factor which contribute to growth of global machine learning market during forecast period. According to the Institute of Electrical and Electronics Engineers, IEEE, (United States), machine learningis highly used in planning for data management. According to the International Data Corporation, IDC, (United States), total of 4.4 zetta bytes (4.4 trn gigabytes) of digital data had been generated in2013. This is expected to reach up to total of 44 zetta bytes (ZB) by the end of 2020.Rise in data generation is expected to increase the demand for machine learning for data management, contributing to growth of global machine learning market during forecast period.

Source: OBRC Analysis

The report on global machine learning market is segmented on the basis of verticals, deployment mode, organization size and services.

Verticals adopting machine learning include:

  • Banking, financial services, and insurance
  • Healthcare and life sciences
  • Retail
  • Telecommunication
  • Government and defense
  • Manufacturing
  • Energy and utilities
  • Other verticals










Deployment modes in machine learning are:

  • Cloud 
  • On-premises




Organization size in machine learning includes:

  • Large enterprises 
  • Small and medium-sized enterprises




Services in machine learning include:

  • Professional services 
  • Managed services




The report scope is widely categorized on the basis of its segments such as verticals, deployment mode, organization size and services. Moreover, the market revenue estimates and forecast includesonly machine learning platform. However, the report scope excludes conventional computer programming.

Geographically, the global machine learning market report has been segmented in:

  • North America (U.S. & Canada)
  • Asia Pacific (China, India, Japan, RoAPAC)
  • Europe (UK, France, Germany, RoE)
  • Rest of World






North America accounted for the largest market share in terms of revenue in 2016 for global machine learning market followed by Asia Pacific and Europe. North America is expected to dominate the market during forecast period. The dominance of North America is witnessed due to maximum adoption of machine learning powered solutions and its early implementation across countries of North America. United States and Canada majorly contributes to the dominance of North America machine learning market during forecast period. However, Asia Pacific is expected to be the fastest growing region in machine learning market during forecast period. Its fastest growth rate is majorly observed due to  high adoption of machine learning among business organizations. Also, increasing machine learning and artificial intelligence startups across Asia Pacific is also boosting the growth rate in machine learning market during forecast period.

Global machine learning market report covers segmentation analysis of verticals, deployment mode, organization size and services. Report further cover segments of verticals which includebanking financial services and insurance, healthcare and life sciences, retail, telecommunication, government and defense, manufacturing, energy and utilities and other verticals. Banking Financial Services and Insurance(BFSI) accounted for the largest market share in terms of revenue for global machine learning market in 2016 and is expected to dominate the market during the forecast period. Its dominance is majorly observed due to capability of machine learning to provide fraud and risk management application which is majorly used in BFSI. Machine learning enables the organization to mitigate fraudulent cases and further make betterinformed decisions and strategies.Deployment modes in machine learning are cloud and on-premises. Organization size in machine learning includes large enterprises and small and medium-sized enterprises. Services in machine learning include professional services and managed services. Managed service is expected to be the fastest growing segment in global machine learning market during forecast period. Its highest growth rate is witnessed due to its ability to help organization to manage its machine learning solutions.Also, managed services take care of all the hardware and software functions via providers.

The major market players of the global machine learning market are:

  • GOOGLE, INC.
  • IBM CORPORATION
  • INTEL CORPORATION
  • MICROSOFT CORPORATION
  • AMAZON WEB SERVICES INC.
  • OTHERS








These companies use various strategies such as merger & acquisition, collaboration, partnership and product launch whereas, product launch is the key strategy adopted by the companies in the global machine learning market.

For example:In 2017, Amazon Web Services Inc. launched AI camera and machine learning tools for businesses (SageMaker-an end-to-end machine learning service). SageMaker supports most popular frameworks in machine learning industry such as Google’s TensorFlow, Facebook’s Caffe2,MXNET, etc. This product launch is expected to increase the market revenue share of company by enhancing its customer base.

In 2017, Amazon Web Services Inc. launched new partner programs for machine learningandnetworking. AWS Solution Provider Programfeatures a number of new incentive models. This is expected to increase the market revenue share of the company by enhancing its customer base.

The report covers detailed analysis of companies which comprises overview, SCOT analysis, product portfolio, strategic initiative, strategic analysis, competitive landscape and market share analysis in the global machine learning market.

Key reasons to buy the report:

  • The report includes market estimation, forecast and analysis for forecast year 2016-2023.
  • Report includes detailed analysis of different segments such as verticals, deployment mode, organization size and services.
  • Identify and understand the strength, opportunities, challenges and threat of global machine learning market during the forecast period.
  • Covers detailed analysis of Porters 5 force model and other strategic models. Also covers revenues, market share analysis, and competitive landscape analysis of major players of the global machine learning market.
  • Detailed analysis of various regulatory policies which are affecting the global machine learning market during the forecast period.







How are we different from others:

At Occams we provide an extensive portfolio which is comprehensive market analysis along with the market size, market share, and market segmentations. Our report on the global machine learningmarket offers detailed analysis of strategic models such as investment vs. adoption model, see-saw analysis and others strategic models. Also, the report contains the detailed analysis of application, adoption scenario and decision support for each segment. The report discusses competitive landscape of the global machine learning market, with giving extensive SCOT analysis of key companies.

Key findings of the global machine learning market:

  • Proliferation in data generation contributes to growth of global machine learning market during the forecast period.
  • Asia Pacific is expected to be the fastest growing region in machine learning market during forecast period.
  • Managed service is expected to be the fastest growing segment in global machine learning market during the forecast period.
  • Product launch is the key strategy adopted by companies in global machine learning market during the forecast period. 
1. INTRODUCTION
1.1. EXECUTIVE SUMMARY
1.2. ESTIMATION METHODOLOGY
 
2. MARKET OVERVIEW
2.1. GLOBAL MACHINE LEARNING MARKET: EVOLUTION & TRANSITION
2.2. MARKET DEFINITION & SCOPE
2.3. INDUSTRY STRUCTURE
2.4. TOTAL MARKET ANALYSIS
2.4.1. TOP 5 FINDINGS
2.4.2. TOP 5 OPPORTUNITY MARKETS
2.4.3. TOP 5 COMPANIES
2.4.4. TOP 3 COMPETITIVE STRATEGIES
2.5. ESTIMATION ANALYSIS
2.6. STRATEGIC ANALYSIS
2.6.1. INVESTMENT VS. ADOPTION MODEL
2.6.2. 360-DEGREE INDUSTRY ANALYSIS
2.6.3. PORTERS 5 FORCE MODEL
2.6.4. SEE-SAW ANALYSIS
2.6.5. CONSUMER ANALYSIS AND KEY BUYING CRITERIA
2.7. COMPETITIVE ANALYSIS
2.7.1. KEY STRATEGIES & ANALYSIS
2.7.2. MARKET SHARE ANALYSIS & TOP COMPANY ANALYSIS
2.8. STRATEGIC RECOMMENDATIONS & KEY CONCLUSIONS
2.8.1. INVESTMENT OPPORTUNITIES BY REGIONS
2.8.2. OPPORTUNITIES IN EMERGING APPLICATIONS
2.8.3. INVESTMENT OPPORTUNITY IN FASTEST GROWING SEGMENT
 
3. MARKET DETERMINANTS 
3.1. MARKET DRIVERS
3.1.1. PROLIFERATION IN DATA GENERATION
3.1.2. TECHNOLOGICAL ADVANCEMENTS IN MACHINE LEARNING 
3.1.3. INCREASING ADOPTION OF CONNECTED DEVICES
3.1.4. INCREASED ADOPTION IN DATA DRIVEN APPLICATION
3.2. MARKET RESTRAINTS
3.2.1. SENSITIVE DATA SECURITY
3.2.2. COMPUTATION LIMITATIONS
3.3. MARKET OPPORTUNITIES
3.3.1. INCREASING DEMAND FOR INTELLIGENT BUSINESS PROCESSES
3.3.2. HIGH DEMAND FROM DIFFERENT END USERS
3.4.   MARKET CHALLENGES
3.4.1. ETHICAL IMPLICATIONS OF ALGORITHMS DEPLOYED
3.4.2. PRONE TO HARDWARE AND SOFTWARE MALFUNCTIONS
 
4. MARKET SEGMENTATION 
4.1. GLOBAL MACHINE LEARNING MARKET BY TYPE OF VERTICAL
4.1.1. MARKET DEFINITION AND SCOPE
4.1.2. DECISION SUPPORT DATABASE & ESTIMATION METHODOLOGY
4.1.3. COMPARATIVE ANALYSIS ACROSS MARKET SEGMENTS
4.1.4. OPPORTUNITY MATRIX
4.1.5. MARKET SEGMENTATION 
4.1.5.1. GLOBALBANKING, FINANCIAL SERVICES, AND INSURANCEMARKET 
4.1.5.1.1. ADOPTION SCENARIO & MARKET DETERMINANTS
4.1.5.1.2. MARKET ESTIMATIONS AND FORECASTS 2014-2023 ($ MILLION)
4.1.5.1.3. KEY PLAYERS & KEY PRODUCTS 
4.1.5.1.4. KEY CONCLUSIONS
4.1.5.2. GLOBAL HEALTHCARE AND LIFE SCIENCESMARKET 
4.1.5.2.1. ADOPTION SCENARIO & MARKET DETERMINANTS
4.1.5.2.2. MARKET ESTIMATIONS AND FORECASTS 2014-2023 ($ MILLION)
4.1.5.2.3. KEY PLAYERS & KEY PRODUCTS 
4.1.5.2.4. KEY CONCLUSIONS
4.1.5.3. GLOBAL RETAILMARKET 
4.1.5.3.1. ADOPTION SCENARIO & MARKET DETERMINANTS
4.1.5.3.2. MARKET ESTIMATIONS AND FORECASTS 2014-2023 ($ MILLION)
4.1.5.3.3. KEY  PLAYERS & KEY PRODUCTS 
4.1.5.3.4. KEY CONCLUSIONS
4.1.5.4. GLOBAL TELECOMMUNICATIONMARKET 
4.1.5.4.1. ADOPTION SCENARIO & MARKET DETERMINANTS
4.1.5.4.2. MARKET ESTIMATIONS AND FORECASTS 2014-2023 ($ MILLION)
4.1.5.4.3. KEY PLAYERS & KEY PRODUCTS 
4.1.5.4.4. KEY CONCLUSIONS
4.1.5.5. GLOBALGOVERNMENT AND DEFENSEMARKET 
4.1.5.5.1. ADOPTION SCENARIO & MARKET DETERMINANTS
4.1.5.5.2. MARKET ESTIMATIONS AND FORECASTS 2014-2023 ($ MILLION)
4.1.5.5.3. KEY PLAYERS & KEY PRODUCTS 
4.1.5.5.4. KEY CONCLUSIONS
4.1.5.6. GLOBALMANUFACTURING MARKET 
4.1.5.6.1. ADOPTION SCENARIO & MARKET DETERMINANTS
4.1.5.6.2. MARKET ESTIMATIONS AND FORECASTS 2014-2023 ($ MILLION)
4.1.5.6.3. KEY PLAYERS & KEY PRODUCTS 
4.1.5.6.4. KEY CONCLUSIONS
4.1.5.7. GLOBALENERGY AND UTILITIES MARKET 
4.1.5.7.1. ADOPTION SCENARIO & MARKET DETERMINANTS
4.1.5.7.2. MARKET ESTIMATIONS AND FORECASTS 2014-2023 ($ MILLION)
4.1.5.7.3. KEY PLAYERS & KEY PRODUCTS 
4.1.5.7.4. KEY CONCLUSIONS
4.1.5.8. GLOBALOTHER VERTICALSMARKET 
4.1.5.8.1. ADOPTION SCENARIO & MARKET DETERMINANTS
4.1.5.8.2. MARKET ESTIMATIONS AND FORECASTS 2014-2023 ($ MILLION)
4.1.5.8.3. KEY PLAYERS & KEY PRODUCTS 
4.1.5.8.4. KEY CONCLUSIONS
4.2. GLOBAL MACHINE LEARNING MARKET BY DEPLOYMENT MODE
4.2.1. MARKET DEFINITION AND SCOPE
4.2.2. DECISION SUPPORT DATABASE & ESTIMATION METHODOLOGY
4.2.3. COMPARATIVE ANALYSIS ACROSS MARKET SEGMENTS
4.2.4. OPPORTUNITY MATRIX
4.2.5. MARKET SEGMENTATION 
4.2.5.1. GLOBALCLOUD MARKET 
4.2.5.1.1. ADOPTION SCENARIO & MARKET DETERMINANTS
4.2.5.1.2. MARKET ESTIMATIONS AND FORECASTS 2014-2023 ($ MILLION)
4.2.5.1.3. KEY PLAYERS & KEY PRODUCTS 
4.2.5.1.4. KEY CONCLUSIONS
4.2.5.2. GLOBALON-PREMISESMARKET 
4.2.5.2.1. ADOPTION SCENARIO & MARKET DETERMINANTS
4.2.5.2.2. MARKET ESTIMATIONS AND FORECASTS 2014-2023 ($ MILLION)
4.2.5.2.3. KEY PLAYERS & KEY PRODUCTS 
4.2.5.2.4. KEY CONCLUSIONS
4.3. GLOBAL MACHINE LEARNING MARKET BY ORGANIZATION SIZE
4.3.1. MARKET DEFINITION AND SCOPE
4.3.2. DECISION SUPPORT DATABASE & ESTIMATION METHODOLOGY
4.3.3. COMPARATIVE ANALYSIS ACROSS MARKET SEGMENTS
4.3.4. OPPORTUNITY MATRIX
4.3.5. MARKET SEGMENTATION 
4.3.5.1. GLOBALLARGE ENTERPRISES MARKET 
4.3.5.1.1. ADOPTION SCENARIO & MARKET DETERMINANTS
4.3.5.1.2. MARKET ESTIMATIONS AND FORECASTS 2014-2023 ($ MILLION)
4.3.5.1.3. KEY PLAYERS & KEY PRODUCTS 
4.3.5.1.4. KEY CONCLUSIONS
4.3.5.2. GLOBALSMALL AND MEDIUM-SIZED ENTERPRISESMARKET 
4.3.5.2.1. ADOPTION SCENARIO & MARKET DETERMINANTS
4.3.5.2.2. MARKET ESTIMATIONS AND FORECASTS 2014-2023 ($ MILLION)
4.3.5.2.3. KEY PLAYERS & KEY PRODUCTS 
4.3.5.2.4. KEY CONCLUSIONS
4.4. GLOBAL MACHINE LEARNING MARKET BY SERVICE 
4.4.1. MARKET DEFINITION AND SCOPE
4.4.2. DECISION SUPPORT DATABASE & ESTIMATION METHODOLOGY
4.4.3. COMPARATIVE ANALYSIS ACROSS MARKET SEGMENTS
4.4.4. OPPORTUNITY MATRIX
4.4.5. MARKET SEGMENTATION 
4.4.5.1. GLOBALPROFESSIONAL SERVICES MARKET 
4.4.5.1.1. ADOPTION SCENARIO & MARKET DETERMINANTS
4.4.5.1.2. MARKET ESTIMATIONS AND FORECASTS 2014-2023 ($ MILLION)
4.4.5.1.3. KEY PLAYERS & KEY PRODUCTS 
4.4.5.1.4. KEY CONCLUSIONS
4.4.5.2. GLOBALMANAGED SERVICESMARKET 
4.4.5.2.1. ADOPTION SCENARIO & MARKET DETERMINANTS
4.4.5.2.2. MARKET ESTIMATIONS AND FORECASTS 2014-2023 ($ MILLION)
4.4.5.2.3. KEY PLAYERS & KEY PRODUCTS 
4.4.5.2.4. KEY CONCLUSIONS
 
5. COMPETITIVE LANDSCAPE
5.1. KEY STRATEGIES
5.1.1. LIST OF MERGERS AND ACQUISITIONS
5.1.2. LIST OF JOINT VENTURES
5.1.3. LIST OF PRODUCT LAUNCHES
5.1.4. LIST OF PARTNERSHIPS
 
6. GEOGRAPHIC ANALYSIS
6.1. DECISION SUPPORT DATABASE & ESTIMATION METHODOLOGY
6.2. COMPARATIVE ANALYSIS ACROSS MARKET SEGMENTS
6.3. OPPORTUNITY MATRIX
6.4. GLOBAL MACHINE LEARNING  MARKET BY REGION 2014-2023 ($ MILLION)
6.4.1. NORTH AMERICA
6.4.1.1. INDUSTRY ANALYSIS 2014-2023 ($ MILLION)
6.4.1.2. TOP COUNTRY ANALYSIS
6.4.1.2.1. U.S. 
6.4.1.2.1.1. MARKET ESTIMATIONS AND FORECASTS 2014-2023 ($ MILLION)
6.4.1.2.1.2. KEY PLAYERS & KEY PRODUCTS
6.4.1.2.1.3. KEY CONCLUSIONS
6.4.1.2.2. CANADA
6.4.1.2.2.1. MARKET ESTIMATIONS AND FORECASTS 2014-2023 ($ MILLION)
6.4.1.2.2.2. KEY PLAYERS & KEY PRODUCTS
6.4.1.2.2.3. KEY CONCLUSIONS
6.4.2. EUROPE
6.4.2.1. INDUSTRY ANALYSIS 2014-2023 ($ MILLION)
6.4.2.2. TOP COUNTRY ANALYSIS
6.4.2.2.1. UK
6.4.2.2.1.1. MARKET ESTIMATIONS AND FORECASTS 2014-2023 ($ MILLION)
6.4.2.2.1.2. KEY PLAYERS & KEY PRODUCTS
6.4.2.2.1.3. KEY CONCLUSIONS
6.4.2.2.2. FRANCE
6.4.2.2.2.1. MARKET ESTIMATIONS AND FORECASTS 2014-2023 ($ MILLION)
6.4.2.2.2.2. KEY PLAYERS & KEY PRODUCTS
6.4.2.2.2.3. KEY CONCLUSIONS
6.4.2.2.3. GERMANY
6.4.2.2.3.1. MARKET ESTIMATIONS AND FORECASTS 2014-2023 ($ MILLION)
6.4.2.2.3.2. KEY PLAYERS & KEY PRODUCTS
6.4.2.2.3.3. KEY CONCLUSIONS
6.4.2.2.4. SPAIN
6.4.2.2.4.1. MARKET ESTIMATIONS AND FORECASTS 2014-2023 ($ MILLION)
6.4.2.2.4.2. KEY PLAYERS & KEY PRODUCTS
6.4.2.2.4.3. KEY CONCLUSIONS
6.4.2.2.5. REST OF EUROPE
6.4.2.2.5.1. MARKET ESTIMATIONS AND FORECASTS 2014-2023 ($ MILLION)
6.4.2.2.5.2. KEY  PLAYERS & KEY PRODUCTS
6.4.2.2.5.3. KEY CONCLUSIONS
6.4.3. ASIA PACIFIC
6.4.3.1. INDUSTRY ANALYSIS 2014-2023 ($ MILLION)
6.4.3.2. TOP COUNTRY ANALYSIS
6.4.3.2.1. CHINA
6.4.3.2.1.1. MARKET ESTIMATIONS AND FORECASTS 2014-2023 ($ MILLION)
6.4.3.2.1.2. KEY PLAYERS & KEY PRODUCTS
6.4.3.2.1.3. KEY CONCLUSIONS
6.4.3.2.2. INDIA
6.4.3.2.2.1. MARKET ESTIMATIONS AND FORECASTS 2014-2023 ($ MILLION)
6.4.3.2.2.2. KEY PLAYERS & KEY PRODUCTS
6.4.3.2.2.3. KEY CONCLUSIONS
6.4.3.2.3. JAPAN
6.4.3.2.3.1. MARKET ESTIMATIONS AND FORECASTS 2014-2023 ($ MILLION)
6.4.3.2.3.2. KEY PLAYERS & KEY PRODUCTS
6.4.3.2.3.3. KEY CONCLUSIONS
6.4.3.2.4. AUSTRALIA
6.4.3.2.4.1. MARKET ESTIMATIONS AND FORECASTS 2014-2023 ($ MILLION)
6.4.3.2.4.2. KEY  PLAYERS & KEY PRODUCTS
6.4.3.2.4.3. KEY CONCLUSIONS
6.4.3.2.5. REST OF ASIA PACIFIC
6.4.3.2.5.1. MARKET ESTIMATIONS AND FORECASTS 2014-2023 ($ MILLION)
6.4.3.2.5.2. KEY  PLAYERS & KEY PRODUCTS
6.4.3.2.5.3. KEY CONCLUSIONS
6.4.4. ROW
6.4.4.1. INDUSTRY ANALYSIS 2014-2023 ($ MILLION)
6.4.4.2. TOP COUNTRY ANALYSIS
6.4.4.2.1. LATIN AMERICA
6.4.4.2.1.1. MARKET ESTIMATIONS AND FORECASTS 2014-2023 ($ MILLION)
6.4.4.2.1.2. KEY PLAYERS & KEY PRODUCTS
6.4.4.2.1.3. KEY CONCLUSIONS
6.4.4.2.2. MIDDLE EAST & AFRICA 
6.4.4.2.2.1. MARKET ESTIMATIONS AND FORECASTS 2014-2023 ($ MILLION)
6.4.4.2.2.2. KEY PLAYERS & KEY PRODUCTS
6.4.4.2.2.3. KEY CONCLUSIONS
 
7. COMPANY PROFILES
7.1. AMAZON WEB SERVICES INC. (U.S.)
7.1.1. OVERVIEW
7.1.2. PRODUCT PORTFOLIO
7.1.3. STRATEGIC INITIATIVES 
7.1.4. SCOT ANALYSIS
7.1.5. STRATEGIC ANALYSIS
7.2. BAIDU, INC. (CHINA)
7.2.1. OVERVIEW
7.2.2. PRODUCT PORTFOLIO
7.2.3. STRATEGIC INITIATIVES 
7.2.4. SCOT ANALYSIS
7.2.5. STRATEGIC ANALYSIS
7.3. DELL INC. (U.S.)
7.3.1. OVERVIEW
7.3.2. PRODUCT PORTFOLIO
7.3.3. STRATEGIC INITIATIVES 
7.3.4. SCOT ANALYSIS
7.3.5. STRATEGIC ANALYSIS
7.4. FAIR ISAAC CORPORATION (U.S.)
7.4.1. OVERVIEW
7.4.2. PRODUCT PORTFOLIO
7.4.3. STRATEGIC INITIATIVES 
7.4.4. SCOT ANALYSIS
7.4.5. STRATEGIC ANALYSIS
7.5. FRACTAL ANALYTICS INC. (U.S.)
7.5.1. OVERVIEW
7.5.2. PRODUCT PORTFOLIO
7.5.3. STRATEGIC INITIATIVES 
7.5.4. SCOT ANALYSIS
7.5.5. STRATEGIC ANALYSIS
7.6. GOOGLE, INC. (U.S.)
7.6.1. OVERVIEW
7.6.2. PRODUCT PORTFOLIO
7.6.3. STRATEGIC INITIATIVES 
7.6.4. SCOT ANALYSIS 
7.6.5. STRATEGIC ANALYSIS
7.7. HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP (U.S.)
7.7.1. OVERVIEW
7.7.2. PRODUCT PORTFOLIO
7.7.3. STRATEGIC INITIATIVES 
7.7.4. SCOT ANALYSIS
7.7.5. STRATEGIC ANALYSIS
7.8. IBM CORPORATION (U.S.)
7.8.1. OVERVIEW
7.8.2. PRODUCT PORTFOLIO
7.8.3. STRATEGIC INITIATIVES 
7.8.4. SCOT ANALYSIS
7.8.5. STRATEGIC ANALYSIS
7.9. INTEL CORPORATION (U.S.)
7.9.1. OVERVIEW
7.9.2. PRODUCT PORTFOLIO
7.9.3. STRATEGIC INITIATIVES 
7.9.4. SCOT ANALYSIS 
7.9.5. STRATEGIC ANALYSIS
7.10. MICROSOFT CORPORATION (U.S.)
7.10.1. OVERVIEW
7.10.2. PRODUCT PORTFOLIO
7.10.3. STRATEGIC INITIATIVES 
7.10.4. SCOT ANALYSIS
7.10.5. STRATEGIC ANALYSIS
7.11. ORACLE CORPORATION (U.S.)
7.11.1. OVERVIEW
7.11.2. PRODUCT PORTFOLIO
7.11.3. STRATEGIC INITIATIVES 
7.11.4. SCOT ANALYSIS
7.11.5. STRATEGIC ANALYSIS
7.12. SAP SE (GERMANY)
7.12.1. OVERVIEW
7.12.2. PRODUCT PORTFOLIO
7.12.3. STRATEGIC INITIATIVES 
7.12.4. SCOT ANALYSIS
7.12.5. STRATEGIC ANALYSIS
7.13. TERADATA (U.S.)
7.13.1. OVERVIEW
7.13.2. PRODUCT PORTFOLIO
7.13.3. STRATEGIC INITIATIVES 
7.13.4. SCOT ANALYSIS
7.13.5. STRATEGIC ANALYSIS
7.14. TIBCO SOFTWARE INC. (U.S.)
7.14.1. OVERVIEW
7.14.2. PRODUCT PORTFOLIO
7.14.3. STRATEGIC INITIATIVES 
7.14.4. SCOT ANALYSIS
7.14.5. STRATEGIC ANALYSIS
7.15. TRADEMARKVISION (U.S.)
7.15.1. OVERVIEW
7.15.2. PRODUCT PORTFOLIO
7.15.3. STRATEGIC INITIATIVES 
7.15.4. SCOT ANALYSIS
7.15.5. STRATEGIC ANALYSIS
 
LIST OF TABLES
1. GLOBAL MACHINE LEARNING MARKET BY VERTICAL2014-2023 ($ MILLION)
2. GLOBAL BANKING, FINANCIAL SERVICES, AND INSURANCE MARKET BY GEOGRAPHY 2014-2023 ($ MILLION)
3. GLOBAL HEALTHCARE AND LIFE SCIENCESMARKET BY GEOGRAPHY 2014-2023 ($ MILLION)
4. GLOBAL RETAILMARKET  BY GEOGRAPHY 2014-2023 ($ MILLION)
5. GLOBALTELECOMMUNICATIONMARKET BY GEOGRAPHY 2014-2023 ($ MILLION)
6. GLOBAL GOVERNMENT AND DEFENSEMARKET BY GEOGRAPHY 2014-2023 ($ MILLION)
7. GLOBAL MANUFACTURINGMARKET BY GEOGRAPHY 2014-2023 ($ MILLION)
8. GLOBAL ENERGY AND UTILITIES MARKET BY GEOGRAPHY 2014-2023 ($ MILLION)
9. GLOBAL OTHER VERTICALS MARKET BY GEOGRAPHY 2014-2023 ($ MILLION)
10. GLOBAL MACHINE LEARNING MARKET BY DEPLOYMENT MODE  2014-2023 ($ MILLION)
11. GLOBAL CLOUDMARKET BY GEOGRAPHY 2014-2023 ($ MILLION)
12. GLOBAL ON-PREMISESMARKET BY GEOGRAPHY 2014-2023 ($ MILLION)
13. GLOBAL MACHINE LEARNING MARKET BY ORGANIZATION SIZE2014-2023 ($ MILLION)
14. GLOBAL LARGE ENTERPRISESMARKET BY GEOGRAPHY 2014-2023 ($ MILLION)
15. GLOBAL SMALL AND MEDIUM-SIZED ENTERPRISESMARKET BY GEOGRAPHY 2014-2023 ($ MILLION)
16. GLOBAL MACHINE LEARNING MARKET BY SERVICE2014-2023 ($ MILLION)
17. GLOBAL PROFESSIONAL SERVICESMARKET BY GEOGRAPHY 2014-2023 ($ MILLION)
18. GLOBAL MANAGED SERVICESMARKET BY GEOGRAPHY 2014-2023 ($ MILLION)
19. NORTH AMERICA MACHINE LEARNING MARKET 2014-2023 ($ MILLION)
20. EUROPE MACHINE LEARNING  MARKET 2014-2023 ($ MILLION)
21. ASIA PACIFIC MACHINE LEARNING MARKET 2014-2023 ($ MILLION)
22. REST OF THE WORLD MACHINE LEARNING MARKET 2014-2023 ($ MILLION)
 
LIST OF FIGURES
1. GLOBAL BANKING, FINANCIAL SERVICES, AND INSURANCE MARKET 2014-2023 ($ MILLION)
2. GLOBAL HEALTHCARE AND LIFE SCIENCESMARKET 2014-2023 ($ MILLION)
3. GLOBAL RETAIL MARKET 2014-2023 ($ MILLION)
4. GLOBALTELECOMMUNICATIONMARKET 2014-2023 ($ MILLION)
5. GLOBAL GOVERNMENT AND DEFENSEMARKET 2014-2023 ($ MILLION)
6. GLOBAL MANUFACTURINGMARKET 2014-2023 ($ MILLION)
7. GLOBAL ENERGY AND UTILITIES MARKET 2014-2023 ($ MILLION)
8. GLOBAL OTHER VERTICALS MARKET 2014-2023 ($ MILLION)
9. GLOBAL CLOUDMARKET 2014-2023 ($ MILLION)
10. GLOBAL ON-PREMISESMARKET 2014-2023 ($ MILLION)
11. GLOBAL LARGE ENTERPRISESMARKET 2014-2023 ($ MILLION)
12. GLOBAL SMALL AND MEDIUM-SIZED ENTERPRISESMARKET 2014-2023 ($ MILLION)
13. GLOBAL PROFESSIONAL SERVICESMARKET 2014-2023 ($ MILLION)
18. GLOBAL MANAGED SERVICESMARKET 2014-2023 ($ MILLION)
19. UNITED STATES (U.S.) MACHINE LEARNING  MARKET 2014-2023 ($ MILLION)
20. CANADA MACHINE LEARNING  MARKET 2014-2023 ($ MILLION)
21. UNITED KINGDOM (UK) MACHINE LEARNING MARKET 2014-2023 ($ MILLION)
22. FRANCE MACHINE LEARNING  MARKET 2014-2023 ($ MILLION)
23. GERMANY MACHINE LEARNING MARKET 2014-2023 ($ MILLION)
24. SPAIN MACHINE LEARNING MARKET 2014-2023 ($ MILLION)
25. ROE MACHINE LEARNING MARKET 2014-2023 ($ MILLION)
26. INDIA MACHINE LEARNING MARKET 2014-2023 ($ MILLION)
27. CHINA MACHINE LEARNING MARKET 2014-2023 ($ MILLION)
28. JAPAN MACHINE LEARNING MARKET 2014-2023 ($ MILLION)
29. AUSTRALIA MACHINE LEARNING MARKET 2014-2023 ($ MILLION)
30. ROAPAC MACHINE LEARNING MARKET 2014-2023 ($ MILLION)
31. LATIN AMERICA MACHINE LEARNING MARKET 2014-2023 ($ MILLION)
32. MENA MACHINE LEARNING MARKET 2014-2023 ($ MILLION)

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