Deep Learning Software Market Synopsis

Global Deep Learning Software Market size is expected to grow from USD 33.8 Billion in 2022 to USD 325 Billion by 2030, at a CAGR of 32.7% during the forecast period (2023-2030).

Deep learning software employs artificial neural networks to mimic the human brain's learning process, enabling computers to recognize patterns and make decisions without explicit programming. It's utilized across various fields such as image and speech recognition, natural language processing, and autonomous vehicles, revolutionizing industries through its ability to handle complex data and tasks.

• A class of machine learning algorithms called deep learning software aims to mimic how the human brain works, enabling computers to learn and make decisions without the need for explicit programming. It's a subset of artificial intelligence (AI) that uses large datasets to train neural networks to find patterns and forecast outcomes. This program is well-known for its ability to learn hierarchical data representations on its own. It does very well in tasks like picture and audio recognition, natural language processing, and complex decision-making.
• Deep learning software has significant effects across a wide range of businesses. Analyzing medical photos helps in illness diagnosis in the healthcare industry. It improves risk assessment and fraud detection in the financial sector. It also permits immediate decision-making for object detection and navigation in autonomous vehicles.
• The benefits of deep learning software include increased productivity, precision, and task automation—tasks that humans previously did. Its transformational potential spans sectors, improving user experiences and stimulating innovation by drawing insightful conclusions from large datasets that may be difficult for people to assess thoroughly.

Deep Learning Software Market Trend Analysis:

Growing Utilization in the Automobile Industry

• The increasing integration of advanced driver assistance systems (ADAS) and autonomous capabilities into cars has made deep learning algorithms essential to enhancing both performance and safety. Deep learning uses vision and sensor data analysis to enable cars to recognize and react to a wide range of road conditions, pedestrians, and other cars. Its significant advancement in autonomous vehicle technology has made it possible for real-time decision-making, effective navigation, and route optimization.
• Deep learning technologies are in more demand as a result of the automobile industry's rising emphasis on connection and intelligent features. Predictive maintenance, fuel economy optimization, and general user experience improvement are all aided by these technologies. Intelligent interactions between humans and machines within automobiles are facilitated by the incorporation of deep learning in fields like computer vision and natural language processing.
• In addition to increasing safety requirements, deep learning software use in the automobile industry also stimulates innovation and competitive dynamics. The deep learning software market is expected to grow significantly due to the continued expenditures in connected cars and autonomous driving technologies. This is because deep learning software plays a crucial part in determining the intelligence and safety of automobiles in the future.

Technology Evolution of Deep Learning

• Deep learning's continuous technical development presents the market with enormous growth potential. Deep learning algorithms get more sophisticated as they advance, enabling the execution of increasingly complex tasks and applications in a variety of sectors. Neural networks are refined by ongoing advancements in model structures and training methodologies, which enhance the functionality of deep learning software. This process of growth opens up new avenues for solving difficult issues and conquering obstacles that were thought to be insurmountable.
• One of the primary factors propelling the market's growth is deep learning's versatility across a variety of fields. The technology's ability to manage unstructured data such as text, audio, and images makes it a flexible solution that can be used in a variety of industries. The continuous development of deep learning enables significant contributions to breakthroughs in fields like diagnostics, fraud detection, predictive maintenance, and other crucial sectors, ranging from healthcare and finance to manufacturing.
• Deep learning's dynamic properties and ability to effectively utilize large datasets make it a game-changer when it comes to gaining insightful knowledge and stimulating creativity. The deep learning market is expected to increase significantly because of the ongoing advancements in technology and its growing application in resolving complex problems in a variety of industries, as well as the growing recognition of these developing capabilities by companies.

Deep Learning Software Market Segment Analysis:

Deep Learning Software Market is Segmented Based on By Component, Application, and End-User Industry.

By Component, Software Segment Is Expected to Dominate the Market During the Forecast Period

• The software category will dominate the market due to several critical reasons driving its growth. The ever-changing technological landscape has increased demand for state-of-the-art software solutions, especially in the deep learning space. Natural language processing, autonomous decision-making, picture and audio recognition, and other fields heavily rely on deep learning software. The growing complexity of tasks and the need for advanced algorithms greatly add to the importance of deep learning software in meeting these needs.

• Additionally, the software market stands out for its scalability and adaptability, which enable companies to integrate and customize solutions to meet their unique needs. This flexibility, together with continuous improvements in algorithmic capabilities, makes deep learning software an essential component for sectors looking to capitalize on AI. As a result, it is anticipated that the software sector will rule the market, driving innovation and determining the course of deep learning applications in a variety of sectors.

By End-User Industry, Automotive Segment Held the Largest Share of 26.5% In 2022

• The automobile business has rapidly transformed due to technology, making the incorporation of deep learning technologies increasingly necessary. Deep learning algorithms are essential to the development of autonomous cars and advanced driver assistance systems (ADAS). They make navigation, object detection, and decision-making in real-time easier.
• Deep learning is being adopted by the automobile industry for purposes other than safety; they include predictive maintenance, enhanced user experiences, and connectivity solutions. Vehicles can see and react to their environment more intelligently, improving overall performance and safety, by utilizing deep learning in the processing of image and sensor data. The automotive sector is expected to maintain its substantial market share through sustained substantial investments in intelligent and autonomous technologies. This segment will also play a pivotal role in driving the market's expansion and contributing to the ongoing evolution of deep learning applications within the automotive landscape.

Deep Learning Software Market Regional Insights:

North America is Expected to Dominate the Market Over the Forecast Period

• The region offers a thriving environment for deep learning applications due to its strong technical infrastructure and high degree of acceptance of innovative ideas. Furthermore, major industry leaders and companies with a concentration on deep learning software are based in North America and are investing heavily in the research and development of cutting-edge technology.
• This leadership is especially noticeable in important industries where deep learning is being used widely, such as healthcare, finance, and the automobile industry. A developed environment, advantageous legal frameworks, and a resolute dedication to technical improvements all contribute to the region's significance. North America is well-positioned to maintain its leadership and steer the market's trajectory as it changes over the coming years as companies and industries there prioritize and incorporate deep learning solutions for increased productivity and creativity.

Key Players Covered in Deep Learning Software Market:

• Advanced Micro Devices, Inc. (U.S.)
• Clarifai, Inc. (U.S.)
• NVIDIA Corporation (U.S.)
• Google Inc. (U.S.)
• IBM Corporation (U.S.)
• Intel Corporation (U.S.)
• Microsoft Corporation (U.S.)
• Amazon Web Services (U.S.)
• SAS Institute Inc. (U.S.)
• Meta Platforms, Inc. (Facebook) (U.S.)
• General Vision (U.S.)
• Sensory Inc. (U.S.)
• Mellanox Technologies, Inc. (U.S.)
• Entilic (U.S.)
• Xilinx (U.S.)
• Micron Technology, Inc. (U.S.)
• KONIKU (U.S.)
• HyperVerge (U.S.)
• RapidMiner (U.S.)
• Qualcomm (U.S.)
• Tenstorrent Inc. (Canada)
• Graphcore (U.K.)
• Huawei Technologies Co., Ltd. (China)
• Fujitsu Ltd (Japan)
• Samsung Electronics Co., Ltd. (South Korea), and Other Major Players.

Key Industry Development in The Deep Learning Software Market:

• In March 2023, NVIDIA and Amazon Web Services, Inc. (AWS) formed a multi-part collaboration aimed at building generative AI applications and improving the AI infrastructure for training increasingly complex Large Language Models (LLMs).
• In May 2022, Intel launched its second-generation Habana AI deep learning processors to deliver high efficiency and high performance. The launch of Habana's new deep learning processors is a key example of Intel executing its AI strategy to give customers a wide array of solution choices from cloud to the edge, addressing the growing number and complex nature of AI workloads

1. INTRODUCTION
   1. RESEARCH OBJECTIVES
   2. RESEARCH METHODOLOGY
   3. RESEARCH PROCESS
   4. SCOPE AND COVERAGE
      1. Market Definition
      2. Key Questions Answered
   5. MARKET SEGMENTATION
2. EXECUTIVE SUMMARY
3. MARKET OVERVIEW
4. GROWTH OPPORTUNITIES BY SEGMENT
5. MARKET LANDSCAPE
   1. PORTER’S FIVE FORCES ANALYSIS
      1. Bargaining Power Of Supplier
      2. Threat Of New Entrants
      3. Threat Of Substitutes
      4. Competitive Rivalry
      5. Bargaining Power Among Buyers
   2. INDUSTRY VALUE CHAIN ANALYSIS
   3. MARKET DYNAMICS
      1. Drivers
      2. Restraints
      3. Opportunities
      4. Challenges
   4. MARKET TREND ANALYSIS
   5. REGULATORY LANDSCAPE
   6. PESTLE ANALYSIS
   7. PRICE TREND ANALYSIS
   8. PATENT ANALYSIS
   9. TECHNOLOGY EVALUATION
   10. MARKET IMPACT OF THE RUSSIA-UKRAINE WAR
       1. Geopolitical Market Disruptions
       2. Supply Chain Disruptions
       3. Instability in Emerging Markets
   11. ECOSYSTEM
6. DEEP LEARNING SOFTWARE MARKET BY COMPONENT (2016-2030)
   1. DEEP LEARNING SOFTWARE MARKET SNAPSHOT AND GROWTH ENGINE
   2. MARKET OVERVIEW
   3. HARDWARE
      1. Introduction And Market Overview
      2. Historic And Forecasted Market Size in Value (2016 – 2030F)
      3. Historic And Forecasted Market Size in Volume (2016 – 2030F)
      4. Key Market Trends, Growth Factors And Opportunities
      5. Geographic Segmentation Analysis
   4. SOFTWARE
   5. SERVICES
7. DEEP LEARNING SOFTWARE MARKET BY APPLICATION (2016-2030)
   1. DEEP LEARNING SOFTWARE MARKET SNAPSHOT AND GROWTH ENGINE
   2. MARKET OVERVIEW
   3. IMAGE RECOGNITION
      1. Introduction And Market Overview
      2. Historic And Forecasted Market Size in Value (2016 – 2030F)
      3. Historic And Forecasted Market Size in Volume (2016 – 2030F)
      4. Key Market Trends, Growth Factors And Opportunities
      5. Geographic Segmentation Analysis
   4. SIGNAL RECOGNITION
   5. DATA MINING
   6. VIDEO SURVEILLANCE & DIAGNOSTICS
   7. MACHINE TRANSLATION
   8. DRUG DISCOVERY
8. DEEP LEARNING SOFTWARE MARKET BY END-USER INDUSTRY (2016-2030)
   1. DEEP LEARNING SOFTWARE MARKET SNAPSHOT AND GROWTH ENGINE
   2. MARKET OVERVIEW
   3. BFSI
      1. Introduction And Market Overview
      2. Historic And Forecasted Market Size in Value (2016 – 2030F)
      3. Historic And Forecasted Market Size in Volume (2016 – 2030F)
      4. Key Market Trends, Growth Factors And Opportunities
      5. Geographic Segmentation Analysis
   4. AUTOMOTIVE
   5. HEALTHCARE
   6. AEROSPACE AND DEFENSE
   7. RETAIL & E-COMMERCE
   8. OTHERS
9. COMPANY PROFILES AND COMPETITIVE ANALYSIS
   1. COMPETITIVE LANDSCAPE
      1. Competitive Positioning
      2. Deep Learning Software Market Share By Manufacturer (2022)
      3. Industry BCG Matrix
      4. Heat Map Analysis
      5. Mergers & Acquisitions
   2. ADVANCED MICRO DEVICES, INC. (U.S.)
      1. Company Overview
      2. Key Executives
      3. Company Snapshot
      4. Role of the Company in the Market
      5. Sustainability and Social Responsibility
      6. Operating Business Segments
      7. Product Portfolio
      8. Business Performance (Production Volume, Sales Volume, Sales Margin, Production Capacity, Capacity Utilization Rate)
      9. Key Strategic Moves And Recent Developments
      10. SWOT Analysis
   3. CLARIFAI, INC. (U.S.)
   4. NVIDIA CORPORATION (U.S.)
   5. GOOGLE INC. (U.S.)
   6. IBM CORPORATION (U.S.)
   7. INTEL CORPORATION (U.S.)
   8. MICROSOFT CORPORATION (U.S.)
   9. AMAZON WEB SERVICES (U.S.)
   10. SAS INSTITUTE INC. (U.S.)
   11. META PLATFORMS, INC. (FACEBOOK) (U.S.)
   12. GENERAL VISION (U.S.)
   13. SENSORY INC. (U.S.)
   14. MELLANOX TECHNOLOGIES, INC. (U.S.)
   15. ENTILIC (U.S.)
   16. XILINX (U.S.)
   17. MICRON TECHNOLOGY, INC. (U.S.)
   18. KONIKU (U.S.)
   19. HYPERVERGE (U.S.)
   20. RAPIDMINER (U.S.)
   21. QUALCOMM (U.S.)
   22. TENSTORRENT INC. (CANADA)
   23. GRAPHCORE (U.K.)
   24. HUAWEI TECHNOLOGIES CO., LTD. (CHINA)
   25. FUJITSU LTD (JAPAN)
   26. SAMSUNG ELECTRONICS CO., LTD. (SOUTH KOREA)
10. GLOBAL DEEP LEARNING SOFTWARE MARKET BY REGION
    1. OVERVIEW
    2. NORTH AMERICA
       1. Key Market Trends, Growth Factors And Opportunities
       2. Key Manufacturers
       3. Historic And Forecasted Market Size By Component
       4. Historic And Forecasted Market Size By Application
       5. Historic And Forecasted Market Size By End-User Industry
       6. Historic And Forecasted Market Size By Country
          1. USA
          2. Canada
          3. Mexico
    3. EASTERN EUROPE
       1. Key Market Trends, Growth Factors And Opportunities
       2. Key Manufacturers
       3. Historic And Forecasted Market Size By Segments
       4. Historic And Forecasted Market Size By Country
          1. Russia
          2. Bulgaria
          3. The Czech Republic
          4. Hungary
          5. Poland
          6. Romania
          7. Rest Of Eastern Europe
    4. WESTERN EUROPE
       1. Key Market Trends, Growth Factors And Opportunities
       2. Key Manufacturers
       3. Historic And Forecasted Market Size By Segments
       4. Historic And Forecasted Market Size By Country
          1. Germany
          2. United Kingdom
          3. France
          4. The Netherlands
          5. Italy
          6. Spain
          7. Rest Of Western Europe
    5. ASIA PACIFIC
       1. Key Market Trends, Growth Factors And Opportunities
       2. Key Manufacturers
       3. Historic And Forecasted Market Size By Segments
       4. Historic And Forecasted Market Size By Country
          1. China
          2. India
          3. Japan
          4. South Korea
          5. Malaysia
          6. Thailand
          7. Vietnam
          8. The Philippines
          9. Australia
          10. New-Zealand
          11. Rest Of APAC
    6. MIDDLE EAST & AFRICA
       1. Key Market Trends, Growth Factors And Opportunities
       2. Key Manufacturers
       3. Historic And Forecasted Market Size By Segments
       4. Historic And Forecasted Market Size By Country
          1. Turkey
          2. Bahrain
          3. Kuwait
          4. Saudi Arabia
          5. Qatar
          6. UAE
          7. Israel
          8. South Africa
    7. SOUTH AMERICA
       1. Key Market Trends, Growth Factors And Opportunities
       2. Key Manufacturers
       3. Historic And Forecasted Market Size By Segments
       4. Historic And Forecasted Market Size By Country
          1. Brazil
          2. Argentina
          3. Rest of South America
11. INVESTMENT ANALYSIS
12. ANALYST VIEWPOINT AND CONCLUSION
    1. Recommendations and Concluding Analysis
    2. Potential Market Strategies

LIST OF TABLES

TABLE 001. EXECUTIVE SUMMARY
TABLE 002. DEEP LEARNING SOFTWARE MARKET BARGAINING POWER OF SUPPLIERS
TABLE 003. DEEP LEARNING SOFTWARE MARKET BARGAINING POWER OF CUSTOMERS
TABLE 004. DEEP LEARNING SOFTWARE MARKET COMPETITIVE RIVALRY
TABLE 005. DEEP LEARNING SOFTWARE MARKET THREAT OF NEW ENTRANTS
TABLE 006. DEEP LEARNING SOFTWARE MARKET THREAT OF SUBSTITUTES
TABLE 007. DEEP LEARNING SOFTWARE MARKET BY TYPE
TABLE 008. ON-PREMISE MARKET OVERVIEW (2016-2028)
TABLE 009. CLOUD-BASED MARKET OVERVIEW (2016-2028)
TABLE 010. DEEP LEARNING SOFTWARE MARKET BY APPLICATION
TABLE 011. APPLICATION A MARKET OVERVIEW (2016-2028)
TABLE 012. APPLICATION B MARKET OVERVIEW (2016-2028)
TABLE 013. APPLICATION C MARKET OVERVIEW (2016-2028)
TABLE 014. NORTH AMERICA DEEP LEARNING SOFTWARE MARKET, BY TYPE (2016-2028)
TABLE 015. NORTH AMERICA DEEP LEARNING SOFTWARE MARKET, BY APPLICATION (2016-2028)
TABLE 016. N DEEP LEARNING SOFTWARE MARKET, BY COUNTRY (2016-2028)
TABLE 017. EUROPE DEEP LEARNING SOFTWARE MARKET, BY TYPE (2016-2028)
TABLE 018. EUROPE DEEP LEARNING SOFTWARE MARKET, BY APPLICATION (2016-2028)
TABLE 019. DEEP LEARNING SOFTWARE MARKET, BY COUNTRY (2016-2028)
TABLE 020. ASIA PACIFIC DEEP LEARNING SOFTWARE MARKET, BY TYPE (2016-2028)
TABLE 021. ASIA PACIFIC DEEP LEARNING SOFTWARE MARKET, BY APPLICATION (2016-2028)
TABLE 022. DEEP LEARNING SOFTWARE MARKET, BY COUNTRY (2016-2028)
TABLE 023. MIDDLE EAST & AFRICA DEEP LEARNING SOFTWARE MARKET, BY TYPE (2016-2028)
TABLE 024. MIDDLE EAST & AFRICA DEEP LEARNING SOFTWARE MARKET, BY APPLICATION (2016-2028)
TABLE 025. DEEP LEARNING SOFTWARE MARKET, BY COUNTRY (2016-2028)
TABLE 026. SOUTH AMERICA DEEP LEARNING SOFTWARE MARKET, BY TYPE (2016-2028)
TABLE 027. SOUTH AMERICA DEEP LEARNING SOFTWARE MARKET, BY APPLICATION (2016-2028)
TABLE 028. DEEP LEARNING SOFTWARE MARKET, BY COUNTRY (2016-2028)
TABLE 029. MICROSOFT: SNAPSHOT
TABLE 030. MICROSOFT: BUSINESS PERFORMANCE
TABLE 031. MICROSOFT: PRODUCT PORTFOLIO
TABLE 032. MICROSOFT: KEY STRATEGIC MOVES AND DEVELOPMENTS
TABLE 032. GITHUB: SNAPSHOT
TABLE 033. GITHUB: BUSINESS PERFORMANCE
TABLE 034. GITHUB: PRODUCT PORTFOLIO
TABLE 035. GITHUB: KEY STRATEGIC MOVES AND DEVELOPMENTS
TABLE 035. AMAZON WEB SERVICES: SNAPSHOT
TABLE 036. AMAZON WEB SERVICES: BUSINESS PERFORMANCE
TABLE 037. AMAZON WEB SERVICES: PRODUCT PORTFOLIO
TABLE 038. AMAZON WEB SERVICES: KEY STRATEGIC MOVES AND DEVELOPMENTS
TABLE 038. GOOGLE: SNAPSHOT
TABLE 039. GOOGLE: BUSINESS PERFORMANCE
TABLE 040. GOOGLE: PRODUCT PORTFOLIO
TABLE 041. GOOGLE: KEY STRATEGIC MOVES AND DEVELOPMENTS
TABLE 041. CLARIFAI: SNAPSHOT
TABLE 042. CLARIFAI: BUSINESS PERFORMANCE
TABLE 043. CLARIFAI: PRODUCT PORTFOLIO
TABLE 044. CLARIFAI: KEY STRATEGIC MOVES AND DEVELOPMENTS
TABLE 044. IBM: SNAPSHOT
TABLE 045. IBM: BUSINESS PERFORMANCE
TABLE 046. IBM: PRODUCT PORTFOLIO
TABLE 047. IBM: KEY STRATEGIC MOVES AND DEVELOPMENTS
TABLE 047. TRINT: SNAPSHOT
TABLE 048. TRINT: BUSINESS PERFORMANCE
TABLE 049. TRINT: PRODUCT PORTFOLIO
TABLE 050. TRINT: KEY STRATEGIC MOVES AND DEVELOPMENTS
TABLE 050. NCH SOFTWARE: SNAPSHOT
TABLE 051. NCH SOFTWARE: BUSINESS PERFORMANCE
TABLE 052. NCH SOFTWARE: PRODUCT PORTFOLIO
TABLE 053. NCH SOFTWARE: KEY STRATEGIC MOVES AND DEVELOPMENTS
TABLE 053. NUANCE COMMUNICATIONS: SNAPSHOT
TABLE 054. NUANCE COMMUNICATIONS: BUSINESS PERFORMANCE
TABLE 055. NUANCE COMMUNICATIONS: PRODUCT PORTFOLIO
TABLE 056. NUANCE COMMUNICATIONS: KEY STRATEGIC MOVES AND DEVELOPMENTS
TABLE 056. BIGHAND: SNAPSHOT
TABLE 057. BIGHAND: BUSINESS PERFORMANCE
TABLE 058. BIGHAND: PRODUCT PORTFOLIO
TABLE 059. BIGHAND: KEY STRATEGIC MOVES AND DEVELOPMENTS
TABLE 059. HARRIS GEOSPATIAL SOLUTIONS: SNAPSHOT
TABLE 060. HARRIS GEOSPATIAL SOLUTIONS: BUSINESS PERFORMANCE
TABLE 061. HARRIS GEOSPATIAL SOLUTIONS: PRODUCT PORTFOLIO
TABLE 062. HARRIS GEOSPATIAL SOLUTIONS: KEY STRATEGIC MOVES AND DEVELOPMENTS
TABLE 062. NVIDIA: SNAPSHOT
TABLE 063. NVIDIA: BUSINESS PERFORMANCE
TABLE 064. NVIDIA: PRODUCT PORTFOLIO
TABLE 065. NVIDIA: KEY STRATEGIC MOVES AND DEVELOPMENTS
TABLE 065. SAS INSTITUTE: SNAPSHOT
TABLE 066. SAS INSTITUTE: BUSINESS PERFORMANCE
TABLE 067. SAS INSTITUTE: PRODUCT PORTFOLIO
TABLE 068. SAS INSTITUTE: KEY STRATEGIC MOVES AND DEVELOPMENTS
TABLE 068. HIVE: SNAPSHOT
TABLE 069. HIVE: BUSINESS PERFORMANCE
TABLE 070. HIVE: PRODUCT PORTFOLIO
TABLE 071. HIVE: KEY STRATEGIC MOVES AND DEVELOPMENTS
TABLE 071. SIGHT MACHINE: SNAPSHOT
TABLE 072. SIGHT MACHINE: BUSINESS PERFORMANCE
TABLE 073. SIGHT MACHINE: PRODUCT PORTFOLIO
TABLE 074. SIGHT MACHINE: KEY STRATEGIC MOVES AND DEVELOPMENTS
TABLE 074. IMC: SNAPSHOT
TABLE 075. IMC: BUSINESS PERFORMANCE
TABLE 076. IMC: PRODUCT PORTFOLIO
TABLE 077. IMC: KEY STRATEGIC MOVES AND DEVELOPMENTS
TABLE 077. ALIBABA: SNAPSHOT
TABLE 078. ALIBABA: BUSINESS PERFORMANCE
TABLE 079. ALIBABA: PRODUCT PORTFOLIO
TABLE 080. ALIBABA: KEY STRATEGIC MOVES AND DEVELOPMENTS

LIST OF FIGURES

FIGURE 001. YEARS CONSIDERED FOR ANALYSIS
FIGURE 002. SCOPE OF THE STUDY
FIGURE 003. DEEP LEARNING SOFTWARE MARKET OVERVIEW BY REGIONS
FIGURE 004. PORTER'S FIVE FORCES ANALYSIS
FIGURE 005. BARGAINING POWER OF SUPPLIERS
FIGURE 006. COMPETITIVE RIVALRYFIGURE 007. THREAT OF NEW ENTRANTS
FIGURE 008. THREAT OF SUBSTITUTES
FIGURE 009. VALUE CHAIN ANALYSIS
FIGURE 010. PESTLE ANALYSIS
FIGURE 011. DEEP LEARNING SOFTWARE MARKET OVERVIEW BY TYPE
FIGURE 012. ON-PREMISE MARKET OVERVIEW (2016-2028)
FIGURE 013. CLOUD-BASED MARKET OVERVIEW (2016-2028)
FIGURE 014. DEEP LEARNING SOFTWARE MARKET OVERVIEW BY APPLICATION
FIGURE 015. APPLICATION A MARKET OVERVIEW (2016-2028)
FIGURE 016. APPLICATION B MARKET OVERVIEW (2016-2028)
FIGURE 017. APPLICATION C MARKET OVERVIEW (2016-2028)
FIGURE 018. NORTH AMERICA DEEP LEARNING SOFTWARE MARKET OVERVIEW BY COUNTRY (2016-2028)
FIGURE 019. EUROPE DEEP LEARNING SOFTWARE MARKET OVERVIEW BY COUNTRY (2016-2028)
FIGURE 020. ASIA PACIFIC DEEP LEARNING SOFTWARE MARKET OVERVIEW BY COUNTRY (2016-2028)
FIGURE 021. MIDDLE EAST & AFRICA DEEP LEARNING SOFTWARE MARKET OVERVIEW BY COUNTRY (2016-2028)
FIGURE 022. SOUTH AMERICA DEEP LEARNING SOFTWARE MARKET OVERVIEW BY COUNTRY (2016-2028)