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

Methodology/Research Approach

This research study involved the extensive usage of both primary and secondary data sources. The research process involved the study of various factors affecting the industry, including the government policy, market environment, competitive landscape, historical data, present trends in the market, technological innovation, upcoming technologies and the technical progress in related industry, and market risks, opportunities, market barriers and challenges. The following illustrative figure shows the market research methodology applied in this report.

Research Programs/Design

Historical Data (2015-2019)	Industry Trends Competitive Landscape By Company Expansion Mergers and Acquisitions Market Segment by Type by Application By Regions/ Geography	Value Status and Outlook Value for Major Players Market Share Growth Rate Present Situation Analysis Value Market Share Growth Rate Present Situation Analysis
Influencing Factors	Market Environment Government Policy Technological Changes Market Risks	Market Drivers Growing Demand of Downstream Reduction in Cost
Market Forecast (2021-2026)	Overall Size by Type by Application By Regions/Geography	Key Data (Value) Market Share Growth Rate CAGR (2021-2026)

Market Size Estimation

Top-down and bottom-up approaches are used to validate the global Voluntary Carbon Offset market size market and estimate the market size for Company, regions segments, product segments and Application (end users).

The market estimations in this report are based on the marketed sale price of Voluntary Carbon Offset (excluding any discounts provided by the player, distributor, wholesaler or traders). The percentage splits, market share, and breakdowns of the product segments are derived on the basis of weights assigned to each of the segments on the basis of their utilization rate and average sale price. The regional splits of the overall Voluntary Carbon Offset market and its sub-segments are based on the percentage adoption or utilization of the given product in the respective region or country.

Major Company in the market is identified through secondary research and their market revenues determined through primary and secondary research. Secondary research included the research of the annual and financial reports of the top Company; whereas, primary research included extensive interviews of key opinion leaders and industry experts such as experienced front-line staff, directors, CEOs and marketing executives. The percentage splits, market share, Growth Rate and breakdowns of the product markets are determined through using secondary sources and verified through the primary sources.

All possible factors that influence the markets included in this research study have been accounted for, viewed in extensive detail, verified through primary research, and analyzed to get the final quantitative and qualitative data. The market size for top-level markets and sub-segments is normalized, and the effect of inflation, economic downturns, and regulatory & policy changes or other factors are not accounted for in the market forecast. This data is combined and added with detailed inputs and analysis from Market Intellix and presented in this report

The following figure shows an illustrative representation of the overall market size estimation process used for this study.

Market Breakdown and Data Triangulation

After complete market engineering with calculations for market statistics; market size estimations; market forecasting; market breakdown; and data triangulation, extensive primary research was conducted to gather information and verify and validate the critical numbers arrived at. In the complete market engineering process, both top-down and bottom-up approaches were extensively used, along with several data triangulation methods, to perform market estimation and market forecasting for the overall market segments and sub-segments listed in this report. Extensive qualitative and further quantitative analysis is also done from all the numbers arrived at in the complete market engineering process to list key information throughout the report.

Data Source

Secondary Sources

Secondary sources include such as press releases, annual reports, non-profit organizations, industry associations, governmental agencies and customs data, etc. This research study involves the usage of widespread secondary sources, directories, databases such as Bloomberg Business, Wind Info, Hoovers, Factiva (Dow Jones & Company), and TRADING ECONOMICS, and News Network, statista, Federal Reserve Economic Data, annual reports, BIS Statistics, ICIS; company house documents; CAS(American Chemical Society); investor presentations; and SEC filings of companies. Secondary research was used to identify and collect information useful for the extensive, technical, market-oriented, and Hospitals study of the Voluntary Carbon Offset market. It was also used to obtain important information about the top companies, market classification and segmentation according to industry trends to the bottom-most level, and key developments related to market and technology perspectives.

Market Size	Segmental value Geographic Penetration Product Adoption Rate for Different market	Journals, Websites, and Press Releases Annual Reports and SEC Filings Company Websites and Press Releases Public and Paid Databases Market Intellix Data Repository
Market Position of Top Company	Product Financials Geographic value Mix Total Company value Business/Segmental value Mix
Qualitative Analysis	Influence Factors Market Potential Market Risks and Opportunities Industry Trends Geographical Features Government Policies	Company Websites and Press Releases Public and Paid Databases Annual Reports Industry Associations Market Intellix Data Repository

Primary Sources

In the primary research process, various sources from both the supply and demand sides were interviewed to obtain qualitative and quantitative information for this report. The primary sources from the supply side include product Company (and their competitors), opinion leaders, industry experts, research institutions, distributors, dealer and traders, as well as the raw materials suppliers and producers, etc.

The primary sources from the demand side include industry experts such as business leaders, marketing and sales directors, technology and innovation directors, supply chain executive, end use (product buyers), and related key executives from various key companies and organizations operating in the global market.

Primary research was conducted to identify segmentation Type, product price range, product Application, key Company, raw materials supply and the downstream demand, industry status and outlook, and key market dynamics such as risks, influence factors, opportunities, market barriers, industry trends, and key player strategies.

Key Executives Interviewed

Key Data Information from Primary Sources

Primary Sources	Parameters	Key Data
Market Segments(by Application, by Type)	Value by Type Status and Forecast Value by Application Value by Regions, Status and Forecast (2021-2026)	Value Market Share by Type Value Growth Rate by Type Value by Application Percentage and Growth Rate by Application Value Growth Rate and Market Share by Regions Market Size Status and Forecast (2021-2026)
Total Market	Overall Size, Status and Forecast	Market Size Status and Forecast (2021-2026)