Global Deep Learning Market: Drivers, Restraints, Opportunities, Trends, and Forecasts to 2023
Global Deep Learning Market – Global Drivers, Restraints, Opportunities, Trends, and Forecasts up to 2023
Market Overview
Deep learning can be considered as a subset of machine learning and consists of algorithms that allow a software to self-train to execute tasks such as image and speech recognition by exposing multilayered neural networks to bulk data. It can have a profound impact on various industries such as finance, automotive, aerospace, telecommunication and information technology, oil and gas, industrial, defense, media and advertising, medical and others. The increasing research and development activities in this domain is expanding the end use areas for the technology. The factors that contribute to the high market share are parallelization, high computing power, swift improvements in information storage capacity in automotive and healthcare industries. A few major applications for deep learning systems are in autonomous cars, data analytics, cyber security and fraud detection. It has become imperative for both small and big organizations to analyze and extract meaningful information from visual content. Advanced technologies such as graphic processing units are highly accepted in scientific disciplines such as deep learning and data sciences. Valuable insights are extracted from bulk data by using deep learning neural networks to improve customer experience and generate innovative products. The development in artificial intelligence capabilities in natural language processing, computer vision areas and image and speech recognition are driving the growth for deep learning.
The use cases for deep learning is diverse ranging from detecting gene abnormalities and predicting weather patterns to identifying fraudulent insurance claims, stock market analysis, robotics, drones, finance, agriculture. Deep learning systems have wide applications in the banking and financial sector. It helps bank employees expand their capabilities so that they can focus more on customer interactions rather than regular banking transactions. The deep learning software can offer solutions based on a client’s background and history and thus can provide evidence and context-based reasoning for every problem. Industries worldwide are generating enormous data which require high processing power and this data is being generated at an unprecedented rate and volume. This has created an enormous opportunity for deep learning powered applications. A plethora of start-ups are coming up with vertical specific solutions and global corporations are supporting these start-ups to innovate faster.
Market Analysis
According to Infoholic Research, the Global Deep Learning market is expected to grow at a CAGR of 49.93% during the forecast period 2017–2023. The market is driven by factors such as faster processor performance, large training data size, and sophisticated neural nets. The future potential of the market is promising owing to opportunities such as development in big data technologies, expanding end-user base and extensive R&D. The market growth is curbed by restraining factors such as implementation challenges, rigid business models, dearth of skilled data scientists, affordability of organizations and data security concerns and inaccessibility.
Segmentation by Solutions
The market has been segmented and analyzed by the following components: Software and Hardware.
Segmentation by End-Users
The market has been segmented and analyzed by the following end-users: Medical, Automotive, Retail, Finance, IT & Telecommunications, Industrial, Aerospace and Defence, Media and Advertising, Oil, Gas and Energy and Others.
Segmentation by Regions
The market has been segmented and analyzed by the following regions: North America, EMEA, Latin America, APAC and Latin America.
Segmentation by Applications
The market has been segmented and analyzed by the following applications: Image Recognition, Voice Recognition, Video Surveillance and Diagnostics, Data mining and Others.
Benefits
The study covers and analyses the “Global Deep Learning Market”. Bringing out the complete key insights of the industry, the report aims to provide an opportunity for players to understand the latest trends, current market scenario, government initiatives, and technologies related to the market. In addition, it helps the venture capitalists in understanding the companies better and take informed decisions.The report covers drivers, restraints, and opportunities (DRO) affecting the market growth during the forecast period (2017–2023). It also contains an analysis of vendor profiles, which include financial health, business units, key business priorities, SWOT, strategies, and views. The report covers competitive landscape, which includes M&A, joint ventures and collaborations, and competitor comparison analysis. In the vendor profile section, for the companies that are privately held, financial information and revenue of segments will be limited.
Market Overview
Deep learning can be considered as a subset of machine learning and consists of algorithms that allow a software to self-train to execute tasks such as image and speech recognition by exposing multilayered neural networks to bulk data. It can have a profound impact on various industries such as finance, automotive, aerospace, telecommunication and information technology, oil and gas, industrial, defense, media and advertising, medical and others. The increasing research and development activities in this domain is expanding the end use areas for the technology. The factors that contribute to the high market share are parallelization, high computing power, swift improvements in information storage capacity in automotive and healthcare industries. A few major applications for deep learning systems are in autonomous cars, data analytics, cyber security and fraud detection. It has become imperative for both small and big organizations to analyze and extract meaningful information from visual content. Advanced technologies such as graphic processing units are highly accepted in scientific disciplines such as deep learning and data sciences. Valuable insights are extracted from bulk data by using deep learning neural networks to improve customer experience and generate innovative products. The development in artificial intelligence capabilities in natural language processing, computer vision areas and image and speech recognition are driving the growth for deep learning.
The use cases for deep learning is diverse ranging from detecting gene abnormalities and predicting weather patterns to identifying fraudulent insurance claims, stock market analysis, robotics, drones, finance, agriculture. Deep learning systems have wide applications in the banking and financial sector. It helps bank employees expand their capabilities so that they can focus more on customer interactions rather than regular banking transactions. The deep learning software can offer solutions based on a client’s background and history and thus can provide evidence and context-based reasoning for every problem. Industries worldwide are generating enormous data which require high processing power and this data is being generated at an unprecedented rate and volume. This has created an enormous opportunity for deep learning powered applications. A plethora of start-ups are coming up with vertical specific solutions and global corporations are supporting these start-ups to innovate faster.
Market Analysis
According to Infoholic Research, the Global Deep Learning market is expected to grow at a CAGR of 49.93% during the forecast period 2017–2023. The market is driven by factors such as faster processor performance, large training data size, and sophisticated neural nets. The future potential of the market is promising owing to opportunities such as development in big data technologies, expanding end-user base and extensive R&D. The market growth is curbed by restraining factors such as implementation challenges, rigid business models, dearth of skilled data scientists, affordability of organizations and data security concerns and inaccessibility.
Segmentation by Solutions
The market has been segmented and analyzed by the following components: Software and Hardware.
Segmentation by End-Users
The market has been segmented and analyzed by the following end-users: Medical, Automotive, Retail, Finance, IT & Telecommunications, Industrial, Aerospace and Defence, Media and Advertising, Oil, Gas and Energy and Others.
Segmentation by Regions
The market has been segmented and analyzed by the following regions: North America, EMEA, Latin America, APAC and Latin America.
Segmentation by Applications
The market has been segmented and analyzed by the following applications: Image Recognition, Voice Recognition, Video Surveillance and Diagnostics, Data mining and Others.
Benefits
The study covers and analyses the “Global Deep Learning Market”. Bringing out the complete key insights of the industry, the report aims to provide an opportunity for players to understand the latest trends, current market scenario, government initiatives, and technologies related to the market. In addition, it helps the venture capitalists in understanding the companies better and take informed decisions.
1 INDUSTRY OUTLOOK
1.1. Industry Overview
1.2. Industry Trends
1.3. PEST Analysis
2 REPORT OUTLINE
2.1 Report Scope
2.2 Report Summary
2.3 Research Methodology
2.4 Report Assumptions
3 MARKET SNAPSHOT
3.1 Total Addressable Market
3.2 Segmented Addressable Market
3.3 Related Markets
3.3.1 Machine Learning Market
3.3.2 Artificial Intelligence Market
4 MARKET OUTLOOK
4.1 Overview
4.2 Regulatory Bodies and Standards
4.3 Porter 5 (Five) Forces
5 MARKET CHARACTERISTICS
5.1 Neural Network diagram
5.2 Use Cases of Deep Learning
5.3 Market Segmentation
5.4 Market Dynamics
5.4.1 Drivers
5.4.1.1 Faster Processor Performance
5.4.1.2 Large training data size
5.4.1.3 Sophisticated neural nets
5.4.2 Restraints
5.4.2.1 Implementation challenges
5.4.2.2 Rigid business models
5.4.2.3 Dearth of skilled data scientists
5.4.2.4 Affordability of organizations
5.4.2.5 Data security concerns and data inaccessibility
5.4.3 Opportunities
5.4.3.1 Development in Big Data Technologies
5.4.3.2 Expanding End-user Base
5.4.3.3 Extensive R&D
5.5 DRO – Impact Analysis
6 TRENDS, ROADMAP, AND PROJECTS
6.1 Market Trends & Impact
6.2 Technology Roadmap
7 GEOGRAPHIC SEGMENTATION: MARKET SIZE AND ANALYSIS
7.1 Overview
7.1.1 North America
7.1.2 US
7.1.3 Canada
7.2 EMEA
7.2.1 The UK
7.2.2 Germany
7.3 Asia Pacific
7.3.1 India
7.3.2 China
7.3.3 Japan
7.4 Latin America
8 DEEP LEARNING MARKET BY SOLUTIONS
8.1 Software Solutions
8.2 Hardware
9 GLOBAL DEEP LEARNING MARKET BY APPLICATIONS
9.1 Image Recognition
9.2 Voice Recognition
9.3 Video Surveillance and Diagnostics
9.4 Data Mining
9.5 Others
10 GLOBAL DEEP LEARNING MARKET BY END-USERS
10.1 Medical
10.2 Automotive
10.3 Retail
10.4 Finance
10.5 IT & Telecommunication
10.6 Industrial
10.7 Aerospace and Defence
10.8 Media and Advertising
10.9 Oil, Gas and Energy
10.10 Others
11 VENDORS PROFILES
11.1 Microsoft Corporation
11.1.1 Overview
11.1.2 Business Units
11.1.3 Microsoft Corporation in Deep Learning
11.1.4 Business Focus
11.1.5 SWOT Analysis
11.1.6 Business Strategies
11.2 IBM Corporation
11.2.1 Overview
11.2.2 Business Units
11.2.3 Geographic Revenue
11.2.4 IBM Corporation in Deep Learning
11.2.5 Business Focus
11.2.6 SWOT Analysis
11.2.7 Business Strategies
11.3 Amazon Web Services
11.3.1 Overview
11.3.2 Business Units
11.3.3 Geographic Revenue
11.3.4 Amazon Web Services in Deep Learning
11.3.5 Business Focus
11.3.6 SWOT Analysis
11.3.7 Business Strategies
11.4 Google Inc.
11.4.1 Overview
11.4.2 Business Units
11.4.3 Geographic Revenue
11.4.4 Google Inc. in Deep Learning
11.4.5 Business Focus
11.4.6 SWOT Analysis
11.4.7 Business Strategies
11.5 Nvidia Corporation
11.5.1 Overview
11.5.2 Business Units
11.5.3 Geographic Revenue
11.5.4 Nvidia in Deep Learning
11.5.5 Business Focus
11.5.6 SWOT Analysis
11.5.7 Business Strategies
11.6 Hewlett-Packard Development Company, L.P.
11.6.1 Overview
11.6.2 Business Segments
11.6.3 Geographic Revenue
11.6.4 HP in Deep Learning
11.6.5 Business Focus
11.6.6 SWOT Analysis
11.6.7 Business Strategies
11.7 Baidu Inc.
11.7.1 Overview
11.7.2 Business Segments
11.7.3 Geographic Revenue
11.7.4 Baidu Inc. in Deep Learning
11.7.5 Business Focus
11.7.6 SWOT Analysis
11.7.7 Business Strategies
11.8 Intel Corporation
11.8.1 Overview
11.8.2 Business Segments
11.8.3 Geographic Revenue
11.8.4 Intel Corporation in Deep Learning
11.8.5 Business Focus
11.8.6 SWOT Analysis
11.8.7 Business Strategies
12 COMPANIES TO WATCH FOR
12.1 Deepmind Technologies Ltd. (Acquired by Google)
12.1.1 Overview
12.1.2 Deepmind Offerings
12.2 Deep Vision
12.2.1 Overview
12.2.2 Deep Vision Offerings
12.3 Bay Labs
12.3.1 Bay Labs Offerings
Abbreviations
Tables
Table 1 GLOBAL DEEP LEARNING MARKET REVENUE BY REGIONS, 2017-2023 ($MILLION)
Table 2 GLOBAL DEEP LEARNING MARKET REVENUE BY SOLUTIONS, 2017-2023 ($MILLION)
Table 3 GLOBAL DEEP LEARNING MARKET REVENUE BY APPLICATIONS, 2017-2023 ($MILLION)
Table 4 GLOBAL DEEP LEARNING MARKET REVENUE BY END-USERS, 2017-2023 ($MILLION)
Charts
Chart 1 PEST ANALYSIS OF GLOBAL DEEP LEARNING MARKET
Chart 2 RESEARCH METHODOLOGY OF GLOBAL DEEP LEARNING MARKET
Chart 3 GLOBAL DEEP LEARNING MARKET REVENUE, 2017-2023 ($BILLION)
Chart 4 PORTER 5 FORCES ON GLOBAL DEEP LEARNING MARKET
Chart 5 NEURAL NETWORK DIAGRAM
Chart 6 GLOBAL DEEP LEARNING MARKET SEGMENTATION
Chart 7 MARKET DYNAMICS – DRIVERS, RESTRAINTS & OPPORTUNITIES
Chart 8 DRO – IMPACT ANALYSIS OF GLOBAL DEEP LEARNING MARKET
Chart 9 TECHNOLOGY ROADMAP FOR GLOBAL DEEP LEARNING MARKET
Chart 10 GLOBAL DEEP LEARNING MARKET SHARE BY GEOGRAPHIES, 2017 AND 2023
Chart 11 DEEP LEARNING MARKET REVENUE IN NORTH AMERICA, 2017–2023 ($MILLION)
Chart 12 DEEP LEARNING MARKET REVENUE IN EMEA, 2017–2023 ($MILLION)
Chart 13 DEEP LEARNING MARKET REVENUE IN ASIA PACIFIC, 2017–2023 ($MILLION)
Chart 14 DEEP LEARNING MARKET REVENUE IN LATIN AMERICA, 2017–2023 ($MILLION)
Chart 15 DEEP LEARNING MARKET REVENUE BY SOLUTIONS ($MILLION)
Chart 16 GLOBAL DEEP LEARNING MARKET REVENUE BY SOFTWARE SOLUTIONS ($MILLION)
Chart 17 GLOBAL DEEP LEARNING MARKET REVENUE BY HARDWARE SOLUTIONS ($MILLION)
Chart 18 GLOBAL DEEP LEARNING MARKET REVENUE BY APPLICATIONS, 2017–2023 ($MILLION)
Chart 19 GLOBAL DEEP LEARNING MARKET REVENUE BY IMAGE RECOGNITION, 2017–2023 ($MILLION)
Chart 20 GLOBAL DEEP LEARNING MARKET REVENUE BY VOICE RECOGNITION, 2017–2023 ($MILLION)
Chart 21 GLOBAL DEEP LEARNING MARKET REVENUE BY VIEO SURVEILLANCE AND DIAGNOSTICS, 2017–2023 ($MILLION)
Chart 22 GLOBAL DEEP LEARNING MARKET REVENUE BY DATA MINING, 2017–2023 ($MILLION)
Chart 23 GLOBAL DEEP LEARNING MARKET REVENUE BY OTHERS, 2017–2023 ($MILLION)
Chart 24 GLOBAL DEEP LEARNING MARKET REVENUE BY END-USERS, 2017–2023 ($MILLION)
Chart 25 GLOBAL DEEP LEARNING MARKET REVENUE BY MEDICAL, 2017-2023 ($MILLION)
Chart 26 GLOBAL DEEP LEARNING MARKET REVENUE BY AUTOMOTIVE, 2017-2023 ($MILLION)
Chart 27 GLOBAL DEEP LEARNING MARKET REVENUE BY RETAIL, 2017-2023 ($MILLION)
Chart 28 GLOBAL DEEP LEARNING MARKET REVENUE BY FINANCE, 2017-2023 ($MILLION)
Chart 29 GLOBAL DEEP LEARNING MARKET REVENUE BY IT & TELECOMMUNICATION, 2017-2023 ($MILLION)
Chart 30 GLOBAL DEEP LEARNING MARKET REVENUE BY INDUSTRIAL, 2017-2023 ($MILLION)
Chart 31 GLOBAL DEEP LEARNING MARKET REVENUE BY AEROSPACE AND DEFENCE, 2017-2023 ($MILLION)
Chart 32 GLOBAL DEEP LEARNING MARKET REVENUE BY MEDIA AND ADVERTISING, 2017-2023 ($MILLION)
Chart 33 GLOBAL DEEP LEARNING MARKET REVENUE BY OIL, GAS AND ENERGY, 2017-2023 ($MILLION)
Chart 34 GLOBAL DEEP LEARNING MARKET REVENUE BY OTHERS, 2017-2023 ($MILLION)
Chart 35 MICROSOFT CORPORATION: OVERVIEW SNAPSHOT
Chart 36 MICROSOFT CORPORATION: BUSINESS UNITS
Chart 37 MICROSOFT CORPORATION: SWOT ANALYSIS
Chart 38 IBM CORPORATION: OVERVIEW SNAPSHOT
Chart 39 IBM CORPORATION: BUSINESS UNITS
Chart 40 IBM CORPORATION: GEOGRAPHIC REVENUE
Chart 41 IBM CORPORATION: SWOT ANALYSIS
Chart 42 AMAZON WEB SERVICES: OVERVIEW SNAPSHOT
Chart 43 AMAZON WEB SERVICES: BUSINESS UNITS
Chart 44 AMAZON WEB SERVICES: GEOGRAPHIC REVENUE
Chart 45 AMAZON WEB SERVICES: SWOT ANALYSIS
Chart 46 GOOGLE INC.: OVERVIEW SNAPSHOT
Chart 47 GOOGLE INC.: BUSINESS UNITS
Chart 48 GOOGLE INC.: GEOGRAPHIC REVENUE
Chart 49 GOOGLE INC.: SWOT ANALYSIS
Chart 50 HP: OVERVIEW SNAPSHOT
Chart 51 HP: BUSINESS SEGMENTS
Chart 52 HP: REVENUE BY GEOGRAPHIES
Chart 53 HP: SWOT ANALYSIS
1.1. Industry Overview
1.2. Industry Trends
1.3. PEST Analysis
2 REPORT OUTLINE
2.1 Report Scope
2.2 Report Summary
2.3 Research Methodology
2.4 Report Assumptions
3 MARKET SNAPSHOT
3.1 Total Addressable Market
3.2 Segmented Addressable Market
3.3 Related Markets
3.3.1 Machine Learning Market
3.3.2 Artificial Intelligence Market
4 MARKET OUTLOOK
4.1 Overview
4.2 Regulatory Bodies and Standards
4.3 Porter 5 (Five) Forces
5 MARKET CHARACTERISTICS
5.1 Neural Network diagram
5.2 Use Cases of Deep Learning
5.3 Market Segmentation
5.4 Market Dynamics
5.4.1 Drivers
5.4.1.1 Faster Processor Performance
5.4.1.2 Large training data size
5.4.1.3 Sophisticated neural nets
5.4.2 Restraints
5.4.2.1 Implementation challenges
5.4.2.2 Rigid business models
5.4.2.3 Dearth of skilled data scientists
5.4.2.4 Affordability of organizations
5.4.2.5 Data security concerns and data inaccessibility
5.4.3 Opportunities
5.4.3.1 Development in Big Data Technologies
5.4.3.2 Expanding End-user Base
5.4.3.3 Extensive R&D
5.5 DRO – Impact Analysis
6 TRENDS, ROADMAP, AND PROJECTS
6.1 Market Trends & Impact
6.2 Technology Roadmap
7 GEOGRAPHIC SEGMENTATION: MARKET SIZE AND ANALYSIS
7.1 Overview
7.1.1 North America
7.1.2 US
7.1.3 Canada
7.2 EMEA
7.2.1 The UK
7.2.2 Germany
7.3 Asia Pacific
7.3.1 India
7.3.2 China
7.3.3 Japan
7.4 Latin America
8 DEEP LEARNING MARKET BY SOLUTIONS
8.1 Software Solutions
8.2 Hardware
9 GLOBAL DEEP LEARNING MARKET BY APPLICATIONS
9.1 Image Recognition
9.2 Voice Recognition
9.3 Video Surveillance and Diagnostics
9.4 Data Mining
9.5 Others
10 GLOBAL DEEP LEARNING MARKET BY END-USERS
10.1 Medical
10.2 Automotive
10.3 Retail
10.4 Finance
10.5 IT & Telecommunication
10.6 Industrial
10.7 Aerospace and Defence
10.8 Media and Advertising
10.9 Oil, Gas and Energy
10.10 Others
11 VENDORS PROFILES
11.1 Microsoft Corporation
11.1.1 Overview
11.1.2 Business Units
11.1.3 Microsoft Corporation in Deep Learning
11.1.4 Business Focus
11.1.5 SWOT Analysis
11.1.6 Business Strategies
11.2 IBM Corporation
11.2.1 Overview
11.2.2 Business Units
11.2.3 Geographic Revenue
11.2.4 IBM Corporation in Deep Learning
11.2.5 Business Focus
11.2.6 SWOT Analysis
11.2.7 Business Strategies
11.3 Amazon Web Services
11.3.1 Overview
11.3.2 Business Units
11.3.3 Geographic Revenue
11.3.4 Amazon Web Services in Deep Learning
11.3.5 Business Focus
11.3.6 SWOT Analysis
11.3.7 Business Strategies
11.4 Google Inc.
11.4.1 Overview
11.4.2 Business Units
11.4.3 Geographic Revenue
11.4.4 Google Inc. in Deep Learning
11.4.5 Business Focus
11.4.6 SWOT Analysis
11.4.7 Business Strategies
11.5 Nvidia Corporation
11.5.1 Overview
11.5.2 Business Units
11.5.3 Geographic Revenue
11.5.4 Nvidia in Deep Learning
11.5.5 Business Focus
11.5.6 SWOT Analysis
11.5.7 Business Strategies
11.6 Hewlett-Packard Development Company, L.P.
11.6.1 Overview
11.6.2 Business Segments
11.6.3 Geographic Revenue
11.6.4 HP in Deep Learning
11.6.5 Business Focus
11.6.6 SWOT Analysis
11.6.7 Business Strategies
11.7 Baidu Inc.
11.7.1 Overview
11.7.2 Business Segments
11.7.3 Geographic Revenue
11.7.4 Baidu Inc. in Deep Learning
11.7.5 Business Focus
11.7.6 SWOT Analysis
11.7.7 Business Strategies
11.8 Intel Corporation
11.8.1 Overview
11.8.2 Business Segments
11.8.3 Geographic Revenue
11.8.4 Intel Corporation in Deep Learning
11.8.5 Business Focus
11.8.6 SWOT Analysis
11.8.7 Business Strategies
12 COMPANIES TO WATCH FOR
12.1 Deepmind Technologies Ltd. (Acquired by Google)
12.1.1 Overview
12.1.2 Deepmind Offerings
12.2 Deep Vision
12.2.1 Overview
12.2.2 Deep Vision Offerings
12.3 Bay Labs
12.3.1 Bay Labs Offerings
Abbreviations
Tables
Table 1 GLOBAL DEEP LEARNING MARKET REVENUE BY REGIONS, 2017-2023 ($MILLION)
Table 2 GLOBAL DEEP LEARNING MARKET REVENUE BY SOLUTIONS, 2017-2023 ($MILLION)
Table 3 GLOBAL DEEP LEARNING MARKET REVENUE BY APPLICATIONS, 2017-2023 ($MILLION)
Table 4 GLOBAL DEEP LEARNING MARKET REVENUE BY END-USERS, 2017-2023 ($MILLION)
Charts
Chart 1 PEST ANALYSIS OF GLOBAL DEEP LEARNING MARKET
Chart 2 RESEARCH METHODOLOGY OF GLOBAL DEEP LEARNING MARKET
Chart 3 GLOBAL DEEP LEARNING MARKET REVENUE, 2017-2023 ($BILLION)
Chart 4 PORTER 5 FORCES ON GLOBAL DEEP LEARNING MARKET
Chart 5 NEURAL NETWORK DIAGRAM
Chart 6 GLOBAL DEEP LEARNING MARKET SEGMENTATION
Chart 7 MARKET DYNAMICS – DRIVERS, RESTRAINTS & OPPORTUNITIES
Chart 8 DRO – IMPACT ANALYSIS OF GLOBAL DEEP LEARNING MARKET
Chart 9 TECHNOLOGY ROADMAP FOR GLOBAL DEEP LEARNING MARKET
Chart 10 GLOBAL DEEP LEARNING MARKET SHARE BY GEOGRAPHIES, 2017 AND 2023
Chart 11 DEEP LEARNING MARKET REVENUE IN NORTH AMERICA, 2017–2023 ($MILLION)
Chart 12 DEEP LEARNING MARKET REVENUE IN EMEA, 2017–2023 ($MILLION)
Chart 13 DEEP LEARNING MARKET REVENUE IN ASIA PACIFIC, 2017–2023 ($MILLION)
Chart 14 DEEP LEARNING MARKET REVENUE IN LATIN AMERICA, 2017–2023 ($MILLION)
Chart 15 DEEP LEARNING MARKET REVENUE BY SOLUTIONS ($MILLION)
Chart 16 GLOBAL DEEP LEARNING MARKET REVENUE BY SOFTWARE SOLUTIONS ($MILLION)
Chart 17 GLOBAL DEEP LEARNING MARKET REVENUE BY HARDWARE SOLUTIONS ($MILLION)
Chart 18 GLOBAL DEEP LEARNING MARKET REVENUE BY APPLICATIONS, 2017–2023 ($MILLION)
Chart 19 GLOBAL DEEP LEARNING MARKET REVENUE BY IMAGE RECOGNITION, 2017–2023 ($MILLION)
Chart 20 GLOBAL DEEP LEARNING MARKET REVENUE BY VOICE RECOGNITION, 2017–2023 ($MILLION)
Chart 21 GLOBAL DEEP LEARNING MARKET REVENUE BY VIEO SURVEILLANCE AND DIAGNOSTICS, 2017–2023 ($MILLION)
Chart 22 GLOBAL DEEP LEARNING MARKET REVENUE BY DATA MINING, 2017–2023 ($MILLION)
Chart 23 GLOBAL DEEP LEARNING MARKET REVENUE BY OTHERS, 2017–2023 ($MILLION)
Chart 24 GLOBAL DEEP LEARNING MARKET REVENUE BY END-USERS, 2017–2023 ($MILLION)
Chart 25 GLOBAL DEEP LEARNING MARKET REVENUE BY MEDICAL, 2017-2023 ($MILLION)
Chart 26 GLOBAL DEEP LEARNING MARKET REVENUE BY AUTOMOTIVE, 2017-2023 ($MILLION)
Chart 27 GLOBAL DEEP LEARNING MARKET REVENUE BY RETAIL, 2017-2023 ($MILLION)
Chart 28 GLOBAL DEEP LEARNING MARKET REVENUE BY FINANCE, 2017-2023 ($MILLION)
Chart 29 GLOBAL DEEP LEARNING MARKET REVENUE BY IT & TELECOMMUNICATION, 2017-2023 ($MILLION)
Chart 30 GLOBAL DEEP LEARNING MARKET REVENUE BY INDUSTRIAL, 2017-2023 ($MILLION)
Chart 31 GLOBAL DEEP LEARNING MARKET REVENUE BY AEROSPACE AND DEFENCE, 2017-2023 ($MILLION)
Chart 32 GLOBAL DEEP LEARNING MARKET REVENUE BY MEDIA AND ADVERTISING, 2017-2023 ($MILLION)
Chart 33 GLOBAL DEEP LEARNING MARKET REVENUE BY OIL, GAS AND ENERGY, 2017-2023 ($MILLION)
Chart 34 GLOBAL DEEP LEARNING MARKET REVENUE BY OTHERS, 2017-2023 ($MILLION)
Chart 35 MICROSOFT CORPORATION: OVERVIEW SNAPSHOT
Chart 36 MICROSOFT CORPORATION: BUSINESS UNITS
Chart 37 MICROSOFT CORPORATION: SWOT ANALYSIS
Chart 38 IBM CORPORATION: OVERVIEW SNAPSHOT
Chart 39 IBM CORPORATION: BUSINESS UNITS
Chart 40 IBM CORPORATION: GEOGRAPHIC REVENUE
Chart 41 IBM CORPORATION: SWOT ANALYSIS
Chart 42 AMAZON WEB SERVICES: OVERVIEW SNAPSHOT
Chart 43 AMAZON WEB SERVICES: BUSINESS UNITS
Chart 44 AMAZON WEB SERVICES: GEOGRAPHIC REVENUE
Chart 45 AMAZON WEB SERVICES: SWOT ANALYSIS
Chart 46 GOOGLE INC.: OVERVIEW SNAPSHOT
Chart 47 GOOGLE INC.: BUSINESS UNITS
Chart 48 GOOGLE INC.: GEOGRAPHIC REVENUE
Chart 49 GOOGLE INC.: SWOT ANALYSIS
Chart 50 HP: OVERVIEW SNAPSHOT
Chart 51 HP: BUSINESS SEGMENTS
Chart 52 HP: REVENUE BY GEOGRAPHIES
Chart 53 HP: SWOT ANALYSIS
