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According to Research, the global market for Deep Learning for Cognitive Computing should grow from US$ million in 2022 to US$ million by 2029, with a CAGR of % for the period of 2023-2029.
China Deep Learning for Cognitive Computing market should grow from US$ million in 2022 to US$ million by 2029, with a CAGR of % for the period of 2023-2029.
The United States Deep Learning for Cognitive Computing market should grow from US$ million in 2022 to US$ million by 2029, with a CAGR of % for the period of 2023-2029.
In terms of type, Platform segment holds a share about % in 2022 and will reach % in 2029; while in terms of application, Intelligent Automation has a share approximately % in 2022 and will grow at a CAGR % during 2023 and 2029.
The global key manufacturers of Deep Learning for Cognitive Computing include Microsoft, IBM, SAS Institute, Amazon Web Services, CognitiveScale, Numenta, Expert .AI, Cisco and Google LLC, etc. In 2022, the global top five players hold a share approximately % in terms of revenue.
Deep learning enables the system to be self-training to learn how to perform specific tasks. And AI itself is part of a larger area called cognitive computing. In ML, pruning means simplifying, compressing, and optimizing a decision tree by removing sections that are uncritical or redundant.
This report aims to provide a comprehensive study of the global market for Deep Learning for Cognitive Computing. Report Highlights:
(1) Global Deep Learning for Cognitive Computing market size (value), history data from 2018-2022 and forecast data from 2023 to 2029.
(2) Global Deep Learning for Cognitive Computing market competitive situation, revenue and market share, from 2018 to 2022.
(3) China Deep Learning for Cognitive Computing market competitive situation, revenue and market share, from 2018 to 2022.
(4) Global Deep Learning for Cognitive Computing segment by region (or country), key regions cover the United States, Europe, Japan, South Korea, Southeast Asia and India, etc.
(5) Global Deep Learning for Cognitive Computing segment by type and by application and regional segment by type and by application.
(6) Deep Learning for Cognitive Computing industry supply chain, upstream, midstream and downstream analysis.
Market segment by regions, regional analysis covers
North America (United States, Canada and Mexico)
Europe (Germany, France, UK, Russia, Italy and Rest of Europe)
Asia-Pacific (China, Japan, South Korea, India, Southeast Asia, Australia and Rest of Asia-Pacific)
South America (Brazil, Rest of South America)
Middle East & Africa
Market segment by type, covers
Platform
Services
Market segment by application, can be divided into
Intelligent Automation
Intelligent Virtual Assistants and Chatbots
Behavior Analysis
Biometrics
Market segment by players, this report covers
Microsoft
IBM
SAS Institute
Amazon Web Services
CognitiveScale
Numenta
Expert .AI
Cisco
Google LLC
Tata Consultancy Services
Infosys Limited
BurstIQ Inc
Red Skios
e-Zest Solutions
Vantage Labs
Cognitive Software Group
SparkCognition
1 Market Overview
1.1 Product Overview and Scope of Deep Learning for Cognitive Computing
1.2 Global Deep Learning for Cognitive Computing Market Size and Forecast
1.3 China Deep Learning for Cognitive Computing Market Size and Forecast
1.4 China Market Percentage in Global
1.4.1 By Revenue, China Deep Learning for Cognitive Computing Share in Global Market, 2018-2029
1.4.2 Deep Learning for Cognitive Computing Market Size: China VS Global, 2018-2029
1.5 Deep Learning for Cognitive Computing Market Dynamics
1.5.1 Deep Learning for Cognitive Computing Market Drivers
1.5.2 Deep Learning for Cognitive Computing Market Restraints
1.5.3 Deep Learning for Cognitive Computing Industry Trends
1.5.4 Deep Learning for Cognitive Computing Industry Policy
2 Global Competitive Situation by Company
2.1 Global Deep Learning for Cognitive Computing Revenue by Company (2018-2023)
2.2 Global Deep Learning for Cognitive Computing Participants, Market Position (Tier 1, Tier 2 and Tier 3)
2.3 Global Deep Learning for Cognitive Computing Concentration Ratio
2.4 Global Deep Learning for Cognitive Computing Mergers & Acquisitions, Expansion Plans
2.5 Global Deep Learning for Cognitive Computing Manufacturers Product Type
3 China Competitive Situation by Company
3.1 China Deep Learning for Cognitive Computing Revenue by Company (2018-2023)
3.2 China Deep Learning for Cognitive Computing Deep Learning for Cognitive Computing Participants, Market Position (Tier 1, Tier 2 and Tier 3)
3.3 China Deep Learning for Cognitive Computing, Revenue Percentage of Local Players VS Foreign Manufacturers (2018-2023)
4 Industry Chain Analysis
4.1 Deep Learning for Cognitive Computing Industry Chain
4.2 Deep Learning for Cognitive Computing Upstream Analysis
4.3 Deep Learning for Cognitive Computing Midstream Analysis
4.4 Deep Learning for Cognitive Computing Downstream Analysis
5 Sights by Type
5.1 Deep Learning for Cognitive Computing Classification
5.1.1 Platform
5.1.2 Services
5.2 By Type, Global Deep Learning for Cognitive Computing Market Size & CAGR, 2018 VS 2022 VS 2029
5.3 By Type, Global Deep Learning for Cognitive Computing Revenue, 2018-2029
6 Sights by Application
6.1 Deep Learning for Cognitive Computing Segment by Application
6.1.1 Intelligent Automation
6.1.2 Intelligent Virtual Assistants and Chatbots
6.1.3 Behavior Analysis
6.1.4 Biometrics
6.2 By Application, Global Deep Learning for Cognitive Computing Market Size & CAGR, 2018 VS 2022 VS 2029
6.3 By Application, Global Deep Learning for Cognitive Computing Revenue, 2018-2029
7 Sales Sights by Region
7.1 By Region, Global Deep Learning for Cognitive Computing Market Size, 2018 VS 2022 VS 2029
7.2 By Region, Global Deep Learning for Cognitive Computing Market Size, 2018-2029
7.3 North America
7.3.1 North America Deep Learning for Cognitive Computing Market Size & Forecasts, 2018-2029
7.3.2 By Country, North America Deep Learning for Cognitive Computing Market Size Market Share
7.4 Europe
7.4.1 Europe Deep Learning for Cognitive Computing Market Size & Forecasts, 2018-2029
7.4.2 By Country, Europe Deep Learning for Cognitive Computing Market Size Market Share
7.5 Asia Pacific
7.5.1 Asia Pacific Deep Learning for Cognitive Computing Market Size & Forecasts, 2018-2029
7.5.2 By Country/Region, Asia Pacific Deep Learning for Cognitive Computing Market Size Market Share
7.6 South America
7.6.1 South America Deep Learning for Cognitive Computing Market Size & Forecasts, 2018-2029
7.6.2 By Country, South America Deep Learning for Cognitive Computing Market Size Market Share
7.7 Middle East & Africa
8 Sights by Country Level
8.1 By Country, Global Deep Learning for Cognitive Computing Market Size & CAGR,2018 VS 2022 VS 2029
8.2 By Country, Global Deep Learning for Cognitive Computing Market Size, 2018-2029
8.3 U.S.
8.3.1 U.S. Deep Learning for Cognitive Computing Market Size, 2018-2029
8.3.2 By Company, U.S. Deep Learning for Cognitive Computing Revenue Market Share, 2018-2023
8.3.3 By Type, U.S. Deep Learning for Cognitive Computing Revenue Market Share, 2022 VS 2029
8.3.4 By Application, U.S. Deep Learning for Cognitive Computing Revenue Market Share, 2022 VS 2029
8.4 Europe
8.4.1 Europe Deep Learning for Cognitive Computing Market Size, 2018-2029
8.4.2 By Company, Europe Deep Learning for Cognitive Computing Revenue Market Share, 2018-2023
8.4.3 By Type, Europe Deep Learning for Cognitive Computing Revenue Market Share, 2022 VS 2029
8.4.4 By Application, Europe Deep Learning for Cognitive Computing Revenue Market Share, 2022 VS 2029
8.5 China
8.5.1 China Deep Learning for Cognitive Computing Market Size, 2018-2029
8.5.2 By Company, China Deep Learning for Cognitive Computing Revenue Market Share, 2018-2023
8.5.3 By Type, China Deep Learning for Cognitive Computing Revenue Market Share, 2022 VS 2029
8.5.4 By Application, China Deep Learning for Cognitive Computing Revenue Market Share, 2022 VS 2029
8.6 Japan
8.6.1 Japan Deep Learning for Cognitive Computing Market Size, 2018-2029
8.6.2 By Company, Japan Deep Learning for Cognitive Computing Revenue Market Share, 2018-2023
8.6.3 By Type, Japan Deep Learning for Cognitive Computing Revenue Market Share, 2022 VS 2029
8.6.4 By Application, Japan Deep Learning for Cognitive Computing Revenue Market Share, 2022 VS 2029
8.7 South Korea
8.7.1 South Korea Deep Learning for Cognitive Computing Market Size, 2018-2029
8.7.2 By Company, South Korea Deep Learning for Cognitive Computing Revenue Market Share, 2018-2023
8.7.3 By Type, South Korea Deep Learning for Cognitive Computing Revenue Market Share, 2022 VS 2029
8.7.4 By Application, South Korea Deep Learning for Cognitive Computing Revenue Market Share, 2022 VS 2029
8.8 Southeast Asia
8.8.1 Southeast Asia Deep Learning for Cognitive Computing Market Size, 2018-2029
8.8.2 By Company, Southeast Asia Deep Learning for Cognitive Computing Revenue Market Share, 2018-2023
8.8.3 By Type, Southeast Asia Deep Learning for Cognitive Computing Revenue Market Share, 2022 VS 2029
8.8.4 By Application, Southeast Asia Deep Learning for Cognitive Computing Revenue Market Share, 2022 VS 2029
8.9 India
8.9.1 India Deep Learning for Cognitive Computing Market Size, 2018-2029
8.9.2 By Company, India Deep Learning for Cognitive Computing Revenue Market Share, 2018-2023
8.9.3 By Type, India Deep Learning for Cognitive Computing Revenue Market Share, 2022 VS 2029
8.9.4 By Application, India Deep Learning for Cognitive Computing Revenue Market Share, 2022 VS 2029
8.10 Middle East & Asia
8.10.1 Middle East & Asia Deep Learning for Cognitive Computing Market Size, 2018-2029
8.10.2 By Company, Middle East & Asia Deep Learning for Cognitive Computing Revenue Market Share, 2018-2023
8.10.3 By Type, Middle East & Asia Deep Learning for Cognitive Computing Revenue Market Share, 2022 VS 2029
8.10.4 By Application, Middle East & Asia Deep Learning for Cognitive Computing Revenue Market Share, 2022 VS 2029
9 Global Manufacturers Profile
9.1 Microsoft
9.1.1 Microsoft Company Information, Head Office, Market Area and Industry Position
9.1.2 Microsoft Company Profile and Main Business
9.1.3 Microsoft Deep Learning for Cognitive Computing Models, Specifications and Application
9.1.4 Microsoft Deep Learning for Cognitive Computing Revenue and Gross Margin, 2018-2023
9.1.5 Microsoft Recent Developments
9.2 IBM
9.2.1 IBM Company Information, Head Office, Market Area and Industry Position
9.2.2 IBM Company Profile and Main Business
9.2.3 IBM Deep Learning for Cognitive Computing Models, Specifications and Application
9.2.4 IBM Deep Learning for Cognitive Computing Revenue and Gross Margin, 2018-2023
9.2.5 IBM Recent Developments
9.3 SAS Institute
9.3.1 SAS Institute Company Information, Head Office, Market Area and Industry Position
9.3.2 SAS Institute Company Profile and Main Business
9.3.3 SAS Institute Deep Learning for Cognitive Computing Models, Specifications and Application
9.3.4 SAS Institute Deep Learning for Cognitive Computing Revenue and Gross Margin, 2018-2023
9.3.5 SAS Institute Recent Developments
9.4 Amazon Web Services
9.4.1 Amazon Web Services Company Information, Head Office, Market Area and Industry Position
9.4.2 Amazon Web Services Company Profile and Main Business
9.4.3 Amazon Web Services Deep Learning for Cognitive Computing Models, Specifications and Application
9.4.4 Amazon Web Services Deep Learning for Cognitive Computing Revenue and Gross Margin, 2018-2023
9.4.5 Amazon Web Services Recent Developments
9.5 CognitiveScale
9.5.1 CognitiveScale Company Information, Head Office, Market Area and Industry Position
9.5.2 CognitiveScale Company Profile and Main Business
9.5.3 CognitiveScale Deep Learning for Cognitive Computing Models, Specifications and Application
9.5.4 CognitiveScale Deep Learning for Cognitive Computing Revenue and Gross Margin, 2018-2023
9.5.5 CognitiveScale Recent Developments
9.6 Numenta
9.6.1 Numenta Company Information, Head Office, Market Area and Industry Position
9.6.2 Numenta Company Profile and Main Business
9.6.3 Numenta Deep Learning for Cognitive Computing Models, Specifications and Application
9.6.4 Numenta Deep Learning for Cognitive Computing Revenue and Gross Margin, 2018-2023
9.6.5 Numenta Recent Developments
9.7 Expert .AI
9.7.1 Expert .AI Company Information, Head Office, Market Area and Industry Position
9.7.2 Expert .AI Company Profile and Main Business
9.7.3 Expert .AI Deep Learning for Cognitive Computing Models, Specifications and Application
9.7.4 Expert .AI Deep Learning for Cognitive Computing Revenue and Gross Margin, 2018-2023
9.7.5 Expert .AI Recent Developments
9.8 Cisco
9.8.1 Cisco Company Information, Head Office, Market Area and Industry Position
9.8.2 Cisco Company Profile and Main Business
9.8.3 Cisco Deep Learning for Cognitive Computing Models, Specifications and Application
9.8.4 Cisco Deep Learning for Cognitive Computing Revenue and Gross Margin, 2018-2023
9.8.5 Cisco Recent Developments
9.9 Google LLC
9.9.1 Google LLC Company Information, Head Office, Market Area and Industry Position
9.9.2 Google LLC Company Profile and Main Business
9.9.3 Google LLC Deep Learning for Cognitive Computing Models, Specifications and Application
9.9.4 Google LLC Deep Learning for Cognitive Computing Revenue and Gross Margin, 2018-2023
9.9.5 Google LLC Recent Developments
9.10 Tata Consultancy Services
9.10.1 Tata Consultancy Services Company Information, Head Office, Market Area and Industry Position
9.10.2 Tata Consultancy Services Company Profile and Main Business
9.10.3 Tata Consultancy Services Deep Learning for Cognitive Computing Models, Specifications and Application
9.10.4 Tata Consultancy Services Deep Learning for Cognitive Computing Revenue and Gross Margin, 2018-2023
9.10.5 Tata Consultancy Services Recent Developments
9.11 Infosys Limited
9.11.1 Infosys Limited Company Information, Head Office, Market Area and Industry Position
9.11.2 Infosys Limited Company Profile and Main Business
9.11.3 Infosys Limited Deep Learning for Cognitive Computing Models, Specifications and Application
9.11.4 Infosys Limited Deep Learning for Cognitive Computing Revenue and Gross Margin, 2018-2023
9.11.5 Infosys Limited Recent Developments
9.12 BurstIQ Inc
9.12.1 BurstIQ Inc Company Information, Head Office, Market Area and Industry Position
9.12.2 BurstIQ Inc Company Profile and Main Business
9.12.3 BurstIQ Inc Deep Learning for Cognitive Computing Models, Specifications and Application
9.12.4 BurstIQ Inc Deep Learning for Cognitive Computing Revenue and Gross Margin, 2018-2023
9.12.5 BurstIQ Inc Recent Developments
9.13 Red Skios
9.13.1 Red Skios Company Information, Head Office, Market Area and Industry Position
9.13.2 Red Skios Company Profile and Main Business
9.13.3 Red Skios Deep Learning for Cognitive Computing Models, Specifications and Application
9.13.4 Red Skios Deep Learning for Cognitive Computing Revenue and Gross Margin, 2018-2023
9.13.5 Red Skios Recent Developments
9.14 e-Zest Solutions
9.14.1 e-Zest Solutions Company Information, Head Office, Market Area and Industry Position
9.14.2 e-Zest Solutions Company Profile and Main Business
9.14.3 e-Zest Solutions Deep Learning for Cognitive Computing Models, Specifications and Application
9.14.4 e-Zest Solutions Deep Learning for Cognitive Computing Revenue and Gross Margin, 2018-2023
9.14.5 e-Zest Solutions Recent Developments
9.15 Vantage Labs
9.15.1 Vantage Labs Company Information, Head Office, Market Area and Industry Position
9.15.2 Vantage Labs Company Profile and Main Business
9.15.3 Vantage Labs Deep Learning for Cognitive Computing Models, Specifications and Application
9.15.4 Vantage Labs Deep Learning for Cognitive Computing Revenue and Gross Margin, 2018-2023
9.15.5 Vantage Labs Recent Developments
9.16 Cognitive Software Group
9.16.1 Cognitive Software Group Company Information, Head Office, Market Area and Industry Position
9.16.2 Cognitive Software Group Company Profile and Main Business
9.16.3 Cognitive Software Group Deep Learning for Cognitive Computing Models, Specifications and Application
9.16.4 Cognitive Software Group Deep Learning for Cognitive Computing Revenue and Gross Margin, 2018-2023
9.16.5 Cognitive Software Group Recent Developments
9.17 SparkCognition
9.17.1 SparkCognition Company Information, Head Office, Market Area and Industry Position
9.17.2 SparkCognition Company Profile and Main Business
9.17.3 SparkCognition Deep Learning for Cognitive Computing Models, Specifications and Application
9.17.4 SparkCognition Deep Learning for Cognitive Computing Revenue and Gross Margin, 2018-2023
9.17.5 SparkCognition Recent Developments
10 Conclusion
11 Appendix
11.1 Research Methodology
11.2 Data Source
11.2.1 Secondary Sources
11.2.2 Primary Sources
11.3 Market Estimation Model
11.4 Disclaimer
Research Methodology:
Global Deep Learning for Cognitive Computing Market Size Estimation
To estimate market size and trends, we use a combination of top-down and bottom-up methods. This allows us to evaluate the market from various perspectives—by company, region, product type, and end users.
Our estimates are based on actual sales data, excluding any discounts. Segment breakdowns and market shares are calculated using weighted averages based on usage rates and average prices. Regional insights are determined by how widely a product or service is adopted in each area.
Key companies are identified through secondary sources like industry reports and company filings. We then verify revenue estimates and other key data points through primary research, including interviews with industry experts, company executives, and decision-makers.
We take into account all relevant factors that could influence the market and validate our findings with real-world input. Our final insights combine both qualitative and quantitative data to provide a well-rounded view. Please note, these estimates do not account for unexpected changes such as inflation, economic downturns, or policy shifts.
Data Source
Secondary Sources
This study draws on a wide range of secondary sources, including press releases, annual reports, non-profit organizations, industry associations, government agencies, and customs data. We also referred to reputable databases and directories such as Bloomberg, Wind Info, Hoovers, Factiva, Trading Economics, Statista, and others. Additional references include investor presentations, company filings (e.g., SEC), economic data, and documents from regulatory and industry bodies.
These sources were used to gather technical and market-focused insights, identify key players, analyze market segmentation and classification, and track major trends and developments across industries.
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Qualitative Analysis |
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Primary Sources
As part of our primary research, we interviewed a variety of stakeholders from both the supply and demand sides to gather valuable qualitative and quantitative insights.
On the supply side, we spoke with product manufacturers, competitors, industry experts, research institutions, distributors, traders, and raw material suppliers. On the demand side, we engaged with business leaders, marketing and sales heads, technology and innovation directors, supply chain executives, and end users across key organizations.
These conversations helped us better understand market segmentation, pricing, applications, leading players, supply chains, demand trends, industry outlook, and key market dynamics—including risks, opportunities, barriers, and strategic developments.
Key Data Information from Primary Sources
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Total Market |
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