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The global deep learning market is expected to witness impressive growth in the forecast period, 2023-2027. Decreasing hardware costs, enhanced need for high computational power, and increased usage of cloud-based technologies are driving the demand for the global deep learning market.
A neural network with three or more layers is used in deep learning, a subset of machine learning. Deep learning learns by analyzing a lot of data to find relevant information. Deep learning technology improves automation, powers artificial intelligence apps and services, and automates the performance of mental and physical tasks. Due to the rising demand for applications and services that attempt to enhance the customer experience, deep learning technology is predicted to enjoy significant demand in the projected period. The demand for high-computing-power technologies is being fueled by the increase in IoT device application across numerous industries. Large amounts of data are produced when well-known industry verticals switch to online platforms to improve transparency and give employees access to firm information. A deep learning system offers scalable and adaptable insights to businesses. The solutions are reasonable and aid in real-time information processing, enabling businesses to make quicker and more informed decisions.
The global deep learning market is segmented on the basis of offering, application, end-user industry, architecture, competitive landscape, and regional distribution. Based on offering, the market is divided into hardware, software, and services. The hardware segment is expected to capture the highest market share in the forecast period, 2023-2027. Deep learning technology requires a massive amount of computing power. Graphical processing units are needed to handle large volumes of calculation in multiple cores and have high memory processing capacity.
Key players operating in the global deep learning market are Amazon Web Services (AWS), Google Inc., IBM Corporation, Intel Corporation, Micron Technology, Microsoft Corporation, Nvidia Corporation, Qualcomm, Samsung Electronics, and Sensory Inc., among others.
Years considered for this report:
Historical Years: 2017-2020
Base Year: 2021
Estimated Year: 2022
Forecast Period: 2023–2027
Objective of the Study:
• To analyze the historical growth in the market size of the global deep learning from 2017 to 2021.
• To estimate and forecast the market size of global deep learning market from 2023 to 2027 and growth rate until 2027.
• To classify and forecast the global deep learning market based on offering, application, end user industry, architecture, region, and company.
• To identify the dominant region or segment in the global deep learning market.
• To identify drivers and challenges for the global deep learning market.
• To examine competitive developments such as expansions, new product launches, mergers & acquisitions, etc., in the global deep learning market.
• To identify and analyze the profiles of leading players operating in the global deep learning market.
• To identify key sustainable strategies adopted by market players in global deep learning market.
TechSci Research performed both primary as well as exhaustive secondary research for this study. Initially, TechSci Research sourced a list of manufacturers and service providers across the country. Subsequently, TechSci Research conducted primary research surveys with the identified companies. While interviewing, the respondents were also enquired about their competitors. Through this technique, TechSci Research could include the manufsacturers and service providers who could not be identified due to the limitations of secondary research. TechSci Research analyzed manufacturers, service providers and presence of all major players across the country.
TechSci Research calculated the market size of the Global deep learning market using a top-down approach, wherein data for various end-user segments was recorded and forecast for the future years. TechSci Research sourced these values from the industry experts and company representatives and externally validated through analyzing historical data of these products and applications for getting an appropriate, overall market size. Various secondary sources such as company websites, news articles, press releases, company annual reports, investor presentations and financial reports were also studied by TechSci Research.
Key Target Audience:
• Market research and consulting firms
• Government bodies such as regulating authorities and policy makers
• Organizations, forums, and alliances
The study is useful in providing answers to several critical questions that are important for the industry stakeholders such as manufacturers, service providers, besides allowing them in strategizing investments and capitalizing on market opportunities.
Report Scope:
In this report, global deep learning market has been segmented into following categories, in addition to the industry trends which have also been detailed below:
• Deep Learning Market, By Offering:
o Hardware
o Software
o Services
• Deep Learning Market, By Application:
o Image Recognition
o Signal Recognition
o Data Mining
• Deep Learning Market, By End-User Industry:
o Healthcare
o Retail
o Automotive
o Security
o Manufacturing
o Others
• Deep Learning Market, By Architecture:
o RNN
o CNN
o DBN
o DSN
o GRU
• Deep Learning Market, By Region:
o North America
 United States
 Canada
 Mexico
o Asia-Pacific
 China
 India
 Japan
 South Korea
 Australia
 Singapore
 Malaysia
o Europe
 Germany
 United Kingdom
 France
 Italy
 Spain
 Poland
 Denmark
o South America
 Brazil
 Argentina
 Colombia
 Peru
 Chile
o Middle East & Africa
 Saudi Arabia
 South Africa
 UAE
 Iraq
 Turkey
Competitive Landscape
Company Profiles: Detailed analysis of the major companies present in global deep learning market.
Available Customizations:
With the given market data, TechSci Research offers customizations according to a company’s specific needs. The following customization options are available for the report:
Company Information
• Detailed analysis and profiling of additional market players (up to five).

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目次

1. Product Overview
2. Research Methodology
3. Impact of COVID-19 on Global Deep Learning Market
4. Executive Summary
5. Voice of Customers
5.1.1. Brand Awareness
5.1.2. Factors Considered while Selecting Supplier
5.1.3. Customer Satisfaction Level
5.1.4. Major Challenges Faced
6. Global Deep Learning Market Outlook
6.1. Market Size & Forecast
6.1.1. By Value
6.2. Market Share & Forecast
6.2.1. By Offering (Hardware, Software, and Services),
6.2.2. By Application (Image Recognition, Signal Recognition, and Data Mining)
6.2.3. By End-User Industry (Healthcare, Retail, Automotive, Security, Manufacturing, and Others)
6.2.4. By Architecture (RNN, CNN, DBN, DSN, and GRU)
6.2.5. By Region
6.2.6. By Company
6.3. Product Market Map
7. North America Deep Learning Market Outlook
7.1. Market Size & Forecast
7.1.1. By Value
7.2. Market Share & Forecast
7.2.1. By Offering
7.2.2. By Application
7.2.3. By End-User Industry
7.2.4. By Architecture
7.2.5. By Country
7.3. North America: Country Analysis
7.3.1. United States Deep Learning Market Outlook
7.3.1.1. Market Size & Forecast
7.3.1.1.1. By Value
7.3.1.2. Market Share & Forecast
7.3.1.2.1. By Offering
7.3.1.2.2. By Application
7.3.1.2.3. By End-User Industry
7.3.1.2.4. By Architecture
7.3.2. Canada Deep Learning Market Outlook
7.3.2.1. Market Size & Forecast
7.3.2.1.1. By Value
7.3.2.2. Market Share & Forecast
7.3.2.2.1. By Offering
7.3.2.2.2. By Application
7.3.2.2.3. By End-User Industry
7.3.2.2.4. By Architecture
7.3.3. Mexico Deep Learning Market Outlook
7.3.3.1. Market Size & Forecast
7.3.3.1.1. By Value
7.3.3.2. Market Share & Forecast
7.3.3.2.1. By Offering
7.3.3.2.2. By Application
7.3.3.2.3. By End-User Industry
7.3.3.2.4. By Architecture
8. Asia-Pacific Deep Learning Market Outlook
8.1. Market Size & Forecast
8.1.1. By Value
8.2. Market Share & Forecast
8.2.1. By Offering
8.2.2. By Application
8.2.3. By End-User Industry
8.2.4. By Architecture
8.2.5. By Country
8.3. Asia-Pacific: Country Analysis
8.3.1. China Deep Learning Market Outlook
8.3.1.1. Market Size & Forecast
8.3.1.1.1. By Value
8.3.1.2. Market Share & Forecast
8.3.1.2.1. By Offering
8.3.1.2.2. By Application
8.3.1.2.3. By End-User Industry
8.3.1.2.4. By Architecture
8.3.2. India Deep Learning Market Outlook
8.3.2.1. Market Size & Forecast
8.3.2.1.1. By Value
8.3.2.2. Market Share & Forecast
8.3.2.2.1. By Offering
8.3.2.2.2. By Application
8.3.2.2.3. By End-User Industry
8.3.2.2.4. By Architecture
8.3.3. Japan Deep Learning Market Outlook
8.3.3.1. Market Size & Forecast
8.3.3.1.1. By Value
8.3.3.2. Market Share & Forecast
8.3.3.2.1. By Offering
8.3.3.2.2. By Application
8.3.3.2.3. By End-User Industry
8.3.3.2.4. By Architecture
8.3.4. South Korea Deep Learning Market Outlook
8.3.4.1. Market Size & Forecast
8.3.4.1.1. By Value
8.3.4.2. Market Share & Forecast
8.3.4.2.1. By Offering
8.3.4.2.2. By Application
8.3.4.2.3. By End-User Industry
8.3.4.2.4. By Architecture
8.3.5. Australia Deep Learning Market Outlook
8.3.5.1. Market Size & Forecast
8.3.5.1.1. By Value
8.3.5.2. Market Share & Forecast
8.3.5.2.1. By Offering
8.3.5.2.2. By Application
8.3.5.2.3. By End-User Industry
8.3.5.2.4. By Architecture
8.3.6. Singapore Deep Learning Market Outlook
8.3.6.1. Market Size & Forecast
8.3.6.1.1. By Value
8.3.6.2. Market Share & Forecast
8.3.6.2.1. By Offering
8.3.6.2.2. By Application
8.3.6.2.3. By End-User Industry
8.3.6.2.4. By Architecture
8.3.7. Malaysia Deep Learning Market Outlook
8.3.7.1. Market Size & Forecast
8.3.7.1.1. By Value
8.3.7.2. Market Share & Forecast
8.3.7.2.1. By Offering
8.3.7.2.2. By Application
8.3.7.2.3. By End-User Industry
8.3.7.2.4. By Architecture
9. Europe Deep Learning Market Outlook
9.1. Market Size & Forecast
9.1.1. By Value
9.2. Market Share & Forecast
9.2.1. By Offering
9.2.2. By Application
9.2.3. By End-User Industry
9.2.4. By Architecture
9.2.5. By Country
9.3. Europe: Country Analysis
9.3.1. Germany Deep Learning Market Outlook
9.3.1.1. Market Size & Forecast
9.3.1.1.1. By Value
9.3.1.2. Market Share & Forecast
9.3.1.2.1. By Offering
9.3.1.2.2. By Application
9.3.1.2.3. By End-User Industry
9.3.1.2.4. By Architecture
9.3.2. United Kingdom Deep Learning Market Outlook
9.3.2.1. Market Size & Forecast
9.3.2.1.1. By Value
9.3.2.2. Market Share & Forecast
9.3.2.2.1. By Offering
9.3.2.2.2. By Application
9.3.2.2.3. By End-User Industry
9.3.2.2.4. By Architecture
9.3.3. France Deep Learning Market Outlook
9.3.3.1. Market Size & Forecast
9.3.3.1.1. By Value
9.3.3.2. Market Share & Forecast
9.3.3.2.1. By Offering
9.3.3.2.2. By Application
9.3.3.2.3. By End-User Industry
9.3.3.2.4. By Architecture
9.3.4. Italy Deep Learning Market Outlook
9.3.4.1. Market Size & Forecast
9.3.4.1.1. By Value
9.3.4.2. Market Share & Forecast
9.3.4.2.1. By Offering
9.3.4.2.2. By Application
9.3.4.2.3. By End-User Industry
9.3.4.2.4. By Architecture
9.3.5. Spain Deep Learning Market Outlook
9.3.5.1. Market Size & Forecast
9.3.5.1.1. By Value
9.3.5.2. Market Share & Forecast
9.3.5.2.1. By Offering
9.3.5.2.2. By Application
9.3.5.2.3. By End-User Industry
9.3.5.2.4. By Architecture
9.3.6. Poland Deep Learning Market Outlook
9.3.6.1. Market Size & Forecast
9.3.6.1.1. By Value
9.3.6.2. Market Share & Forecast
9.3.6.2.1. By Offering
9.3.6.2.2. By Application
9.3.6.2.3. By End-User Industry
9.3.6.2.4. By Architecture
9.3.7. Denmark Deep Learning Market Outlook
9.3.7.1. Market Size & Forecast
9.3.7.1.1. By Value
9.3.7.2. Market Share & Forecast
9.3.7.2.1. By Offering
9.3.7.2.2. By Application
9.3.7.2.3. By End-User Industry
9.3.7.2.4. By Architecture
10. South America Deep Learning Market Outlook
10.1. Market Size & Forecast
10.1.1. By Value
10.2. Market Share & Forecast
10.2.1. By Offering
10.2.2. By Application
10.2.3. By End-User Industry
10.2.4. By Architecture
10.2.5. By Country
10.3. South America: Country Analysis
10.3.1. Brazil Deep Learning Market Outlook
10.3.1.1. Market Size & Forecast
10.3.1.1.1. By Value
10.3.1.2. Market Share & Forecast
10.3.1.2.1. By Offering
10.3.1.2.2. By Application
10.3.1.2.3. By End-User Industry
10.3.1.2.4. By Architecture
10.3.2. Argentina Deep Learning Market Outlook
10.3.2.1. Market Size & Forecast
10.3.2.1.1. By Value
10.3.2.2. Market Share & Forecast
10.3.2.2.1. By Offering
10.3.2.2.2. By Application
10.3.2.2.3. By End-User Industry
10.3.2.2.4. By Architecture
10.3.3. Colombia Deep Learning Market Outlook
10.3.3.1. Market Size & Forecast
10.3.3.1.1. By Value
10.3.3.2. Market Share & Forecast
10.3.3.2.1. By Offering
10.3.3.2.2. By Application
10.3.3.2.3. By End-User Industry
10.3.3.2.4. By Architecture
10.3.4. Peru Deep Learning Market Outlook
10.3.4.1. Market Size & Forecast
10.3.4.1.1. By Value
10.3.4.2. Market Share & Forecast
10.3.4.2.1. By Offering
10.3.4.2.2. By Application
10.3.4.2.3. By End-User Industry
10.3.4.2.4. By Architecture
10.3.5. Chile Deep Learning Market Outlook
10.3.5.1. Market Size & Forecast
10.3.5.1.1. By Value
10.3.5.2. Market Share & Forecast
10.3.5.2.1. By Offering
10.3.5.2.2. By Application
10.3.5.2.3. By End-User Industry
10.3.5.2.4. By Architecture
11. Middle East & Africa Deep Learning Market Outlook
11.1. Market Size & Forecast
11.1.1. By Value
11.2. Market Share & Forecast
11.2.1. By Offering
11.2.2. By Application
11.2.3. By End-User Industry
11.2.4. By Architecture
11.2.5. By Country
11.3. Middle East & Africa: Country Analysis
11.3.1. Saudi Arabia Deep Learning Market Outlook
11.3.1.1. Market Size & Forecast
11.3.1.1.1. By Value
11.3.1.2. Market Share & Forecast
11.3.1.2.1. By Offering
11.3.1.2.2. By Application
11.3.1.2.3. By End-User Industry
11.3.1.2.4. By Architecture
11.3.2. South Africa Deep Learning Market Outlook
11.3.2.1. Market Size & Forecast
11.3.2.1.1. By Value
11.3.2.2. Market Share & Forecast
11.3.2.2.1. By Offering
11.3.2.2.2. By Application
11.3.2.2.3. By End-User Industry
11.3.2.2.4. By Architecture
11.3.3. UAE Deep Learning Market Outlook
11.3.3.1. Market Size & Forecast
11.3.3.1.1. By Value
11.3.3.2. Market Share & Forecast
11.3.3.2.1. By Offering
11.3.3.2.2. By Application
11.3.3.2.3. By End-User Industry
11.3.3.2.4. By Architecture
11.3.4. Iraq Deep Learning Market Outlook
11.3.4.1. Market Size & Forecast
11.3.4.1.1. By Value
11.3.4.2. Market Share & Forecast
11.3.4.2.1. By Offering
11.3.4.2.2. By Application
11.3.4.2.3. By End-User Industry
11.3.4.2.4. By Architecture
11.3.5. Turkey Deep Learning Market Outlook
11.3.5.1. Market Size & Forecast
11.3.5.1.1. By Value
11.3.5.2. Market Share & Forecast
11.3.5.2.1. By Offering
11.3.5.2.2. By Application
11.3.5.2.3. By End-User Industry
11.3.5.2.4. By Architecture
12. Market Dynamics
12.1. Drivers
12.2. Challenges
13. Market Trends & Developments
14. Company Profiles
14.1. Amazon Web Services (AWS)
14.2. Google Inc.
14.3. IBM Corporation
14.4. Intel Corporation
14.5. Micron Technology
14.6. Microsoft Corporation
14.7. Nvidia Corporation
14.8. Qualcomm
14.9. Samsung Electronics
14.10. Sensory Inc.
15. Strategic Recommendations