Deep Learning Market - Global Industry Size, Share, Trends, Opportunity, and Forecast, 2017-2027 Segmented By Offering (Hardware, Software, and Services), By Application (Image Recognition, Signal Recognition, and Data Mining), By End-User Industry (Healthcare, Retail, Automotive, Security, Manufacturing, and Others), By Architecture (RNN, CNN, DBN, DSN, and GRU), and By Region
The global deep learning market is expected to grow at an impressive CAGR in the forecast period, 2023-2027. Reduction in hardware costs, improvement of computational power, and rise in adoption of cloud-based technology are the primary factors driving the demand for the global deep learning market for the next five years.
Deep learning is a subset of machine learning which involves a neural network with three or more layers. Deep learning learns by processing large amounts of data to extract meaningful information. Deep learning technology enhances the automation process, drives artificial intelligence applications, and services, and performs analytical and physical tasks without human intervention. Deep learning technology is expected to witness massive demand in the forecast period due to an increase in demand for convenience services and applications aiming to improve the consumer experience.
Increased Awareness about Deep Learning Technology Drives the Market Growth
The rise in the adoption of IoT devices across several industries is fueling the demand for technologies having high computational power. Shift to online platforms by prominent industry verticals to increase transparency and access of employees to the company data generates large volumes of data. Deep learning solution provides companies with flexible and scalable insights. The solutions are affordable and help in processing the information in real time, allowing organizations to make informed decisions in less time.
The banking, financial services, and insurance (BFSI) sector create huge growth opportunities for deep learning technology. The BFSI industry stores vast amounts of confidential information that needs to be protected from possible cyberattacks. Deep learning technology is highly secure and takes essential steps to adhere to strict compliance guidelines, ensuring that the data is not lost and is adequately documented.
A rise in the Adoption of Cloud Technology Fuels the Market Demand
With the increase in data generation, the need for tools that can analyze, process, and extract meaningful information is expected to rise. Cloud analytics combines infrastructural, analytical, and technological tools & techniques and aids in obtaining essential data from the dataset. The rapid adoption of cloud-based deep learning platforms eliminates the need to invest in capital and hardware infrastructure and, therefore, is considered highly cost-effective. It also lowers the operational and maintenance costs for organizations. Cloud-based deep learning technology is highly secure and provides enhanced protection to secure critical information of the organization.
Applications in Automotive Industry Support the Market Growth
The flourishing automotive industry and the adoption of attractive features and technologies by automotive manufacturers are expected to create lucrative opportunities for the global deep-learning market in the next five years. Deep learning finds several applications in self-driving cars, connected vehicles, predictive maintenance, driver assistance, quality control, and efficiently managing the supply chain. The advancements in deep learning technology and the growing use of advanced technologies in automobiles are expected to accelerate the global deep learning market growth for the next five years.
Market Segmentation
The global deep learning market is segmented into an offering, application, end-user industry, architecture, company, and regional distribution. Based on the offering, the market is divided into hardware, software, and services. Based on application, the market is divided into image recognition, signal recognition, and data mining. Based on the end-user industry, the market is divided into healthcare, retail, automotive, security, manufacturing, and others. Based on the end user, the market is divided into healthcare, media and entertainment, manufacturing and industrial, retail and e-commerce, transportation, and others. Based on architecture, the market is divided into RNN, CNN, DBN, DSN, and GRU. Also, the market analysis studies the regional segmentation, divided among the Asia-Pacific region, North American region, European region, South American region, and Middle East & African region.
Market Players
Amazon Web Services (AWS), Google Inc., IBM Corporation, Intel Corporation, Micron Technology, Microsoft Corporation, Nvidia Corporation, Qualcomm, Samsung Electronics, and Sensory Inc. are the market players operating in the global deep learning market.
Report Scope:
In this report, the global deep learning market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:
Company Profiles: Detailed analysis of the major companies present in the 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
Deep learning is a subset of machine learning which involves a neural network with three or more layers. Deep learning learns by processing large amounts of data to extract meaningful information. Deep learning technology enhances the automation process, drives artificial intelligence applications, and services, and performs analytical and physical tasks without human intervention. Deep learning technology is expected to witness massive demand in the forecast period due to an increase in demand for convenience services and applications aiming to improve the consumer experience.
Increased Awareness about Deep Learning Technology Drives the Market Growth
The rise in the adoption of IoT devices across several industries is fueling the demand for technologies having high computational power. Shift to online platforms by prominent industry verticals to increase transparency and access of employees to the company data generates large volumes of data. Deep learning solution provides companies with flexible and scalable insights. The solutions are affordable and help in processing the information in real time, allowing organizations to make informed decisions in less time.
The banking, financial services, and insurance (BFSI) sector create huge growth opportunities for deep learning technology. The BFSI industry stores vast amounts of confidential information that needs to be protected from possible cyberattacks. Deep learning technology is highly secure and takes essential steps to adhere to strict compliance guidelines, ensuring that the data is not lost and is adequately documented.
A rise in the Adoption of Cloud Technology Fuels the Market Demand
With the increase in data generation, the need for tools that can analyze, process, and extract meaningful information is expected to rise. Cloud analytics combines infrastructural, analytical, and technological tools & techniques and aids in obtaining essential data from the dataset. The rapid adoption of cloud-based deep learning platforms eliminates the need to invest in capital and hardware infrastructure and, therefore, is considered highly cost-effective. It also lowers the operational and maintenance costs for organizations. Cloud-based deep learning technology is highly secure and provides enhanced protection to secure critical information of the organization.
Applications in Automotive Industry Support the Market Growth
The flourishing automotive industry and the adoption of attractive features and technologies by automotive manufacturers are expected to create lucrative opportunities for the global deep-learning market in the next five years. Deep learning finds several applications in self-driving cars, connected vehicles, predictive maintenance, driver assistance, quality control, and efficiently managing the supply chain. The advancements in deep learning technology and the growing use of advanced technologies in automobiles are expected to accelerate the global deep learning market growth for the next five years.
Market Segmentation
The global deep learning market is segmented into an offering, application, end-user industry, architecture, company, and regional distribution. Based on the offering, the market is divided into hardware, software, and services. Based on application, the market is divided into image recognition, signal recognition, and data mining. Based on the end-user industry, the market is divided into healthcare, retail, automotive, security, manufacturing, and others. Based on the end user, the market is divided into healthcare, media and entertainment, manufacturing and industrial, retail and e-commerce, transportation, and others. Based on architecture, the market is divided into RNN, CNN, DBN, DSN, and GRU. Also, the market analysis studies the regional segmentation, divided among the Asia-Pacific region, North American region, European region, South American region, and Middle East & African region.
Market Players
Amazon Web Services (AWS), Google Inc., IBM Corporation, Intel Corporation, Micron Technology, Microsoft Corporation, Nvidia Corporation, Qualcomm, Samsung Electronics, and Sensory Inc. are the market players operating in the global deep learning market.
Report Scope:
In this report, the global deep learning market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:
- Deep Learning Market, By Offering:
- Hardware
- Software
- Services
- Deep Learning Market, By Application:
- Image Recognition
- Signal Recognition
- Data Mining
- Deep Learning Market, By End-User Industry:
- Healthcare
- Retail
- Automotive
- Security
- Manufacturing
- Others
- Deep Learning Market, By Architecture:
- RNN
- CNN
- DBN
- DSN
- GRU
- Deep Learning Market, By Region:
- North America
- United States
- Canada
- Mexico
- Asia-Pacific
- China
- India
- Japan
- South Korea
- Australia
- Singapore
- Malaysia
- Europe
- Germany
- United Kingdom
- France
- Italy
- Spain
- Poland
- Denmark
- South America
- Brazil
- Argentina
- Colombia
- Peru
- Chile
- Middle East & Africa
- Saudi Arabia
- South Africa
- UAE
- Iraq
- Turkey
Company Profiles: Detailed analysis of the major companies present in the 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).
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. Brand Awareness
5.2. Factors Considered while Selecting Vendor
5.3. Customer Satisfaction Level
5.4. 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 (2021)
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
2. RESEARCH METHODOLOGY
3. IMPACT OF COVID-19 ON GLOBAL DEEP LEARNING MARKET
4. EXECUTIVE SUMMARY
5. VOICE OF CUSTOMERS
5.1. Brand Awareness
5.2. Factors Considered while Selecting Vendor
5.3. Customer Satisfaction Level
5.4. 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 (2021)
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
