The global deep learning market size is expected to reach USD 526.7 billion by 2030, expanding at a CAGR of 33.5% from 2023 to 2030. Deep learning is expected to gain sustainable momentum in the coming years owing to its high computational ability and improved complex data-driven applications. The growing emphasis on big data analytics and the adoption of Artificial Intelligence (AI) in customer-centric services is expected to propel the growth of the deep learning industry over the forecast period.
AI has evolved rapidly in recent years, enabling machines to perform cognitive tasks effectively. The adoption of AI across various sectors has unlocked numerous potential opportunities for machine learning and deep learning applications. Furthermore, AI-as-a-service such as virtual assistants has allowed smaller organizations to implement AI algorithms required for deep learning applications without a large capital investment. Moreover, the availability of a large amount of data and the need for high computing power encourage SMEs and large enterprises to invest significantly in deep learning technology.
Deep learning allows the machine to solve complex problems even if the data is not well organized. A deep learning algorithm performs a task repeatedly, every time tweaking it to improve the outcomes. Thus, the more the task performed by the machines, the better will be the outcome. As a result, large amounts of unstructured data can be analyzed using deep learning algorithms and further deployed to obtain relevant insights for a more reliable decision-making process. For instance, organizations may use deep learning technology to unveil any data pointers between industry insights, social media conversation, and a stock price of a given organization.
Image and voice recognition are some of the leading applications in the deep learning industry. Several online and offline services such as Alexa virtual assistant by Amazon, Microsoft Cortana, and Siri use deep learning to acquire language skills while interacting with people. Facebook and Google have implemented deep learning technology for cognitive image analysis in their image classification application. It helps companies provide relevant results and automatic descriptions related to images.
Besides, deep learning algorithms can recreate a black-and-white image in color, offering impressive and accurate results in image colorization applications. For instance, In June 2019, Amazon introduced a new deep learning model called Alexa Conversations to create natural voice experiences on Alexa.
Deep learning offers lucrative investment opportunities for vendors due to the technology's high adoption rate. As a result, the companies consider product development as one of the strategic initiatives to capture the deep learning industry share. Recently, in February 2020, Google Inc. announced the launch of Reformer, an updated version of the transformer deep-learning model. In February 2020, Concentrix Corporation launched the deep learning algorithm tool for cybersecurity applications.
AI has evolved rapidly in recent years, enabling machines to perform cognitive tasks effectively. The adoption of AI across various sectors has unlocked numerous potential opportunities for machine learning and deep learning applications. Furthermore, AI-as-a-service such as virtual assistants has allowed smaller organizations to implement AI algorithms required for deep learning applications without a large capital investment. Moreover, the availability of a large amount of data and the need for high computing power encourage SMEs and large enterprises to invest significantly in deep learning technology.
Deep learning allows the machine to solve complex problems even if the data is not well organized. A deep learning algorithm performs a task repeatedly, every time tweaking it to improve the outcomes. Thus, the more the task performed by the machines, the better will be the outcome. As a result, large amounts of unstructured data can be analyzed using deep learning algorithms and further deployed to obtain relevant insights for a more reliable decision-making process. For instance, organizations may use deep learning technology to unveil any data pointers between industry insights, social media conversation, and a stock price of a given organization.
Image and voice recognition are some of the leading applications in the deep learning industry. Several online and offline services such as Alexa virtual assistant by Amazon, Microsoft Cortana, and Siri use deep learning to acquire language skills while interacting with people. Facebook and Google have implemented deep learning technology for cognitive image analysis in their image classification application. It helps companies provide relevant results and automatic descriptions related to images.
Besides, deep learning algorithms can recreate a black-and-white image in color, offering impressive and accurate results in image colorization applications. For instance, In June 2019, Amazon introduced a new deep learning model called Alexa Conversations to create natural voice experiences on Alexa.
Deep learning offers lucrative investment opportunities for vendors due to the technology's high adoption rate. As a result, the companies consider product development as one of the strategic initiatives to capture the deep learning industry share. Recently, in February 2020, Google Inc. announced the launch of Reformer, an updated version of the transformer deep-learning model. In February 2020, Concentrix Corporation launched the deep learning algorithm tool for cybersecurity applications.
Deep Learning Market Report Highlights
- The hardware segment is expected to witness the fastest growth over the forecast period owing to the growing demand for deep learning chipsets and reduced hardware costs
- The Field Programmable Gate Array (FPGA) possesses high computational capability and has better power efficiency. As a result, the FPGA segment is expected to expand at the highest CAGR during the forecast period
- Deep learning algorithms exhibit great potential in the automated extraction of complex data, thereby excelling in big data analytics application
- Deep learning holds the potential to revolutionize the healthcare industry in the coming years by applying neural networks to analyze patient datasets to provide better outcomes
- Several government initiatives related to digitalization and the growing adoption of next-generation technologies such as AI and machine learning in the APAC region exhibited the strong growth of deep learning technology
Table of Contents
Chapter 1 Market Segmentation and Scope1.1 Market Segmentation and Scope
1.2 Market Definition
1.3 Information Procurement
1.3.1 Purchased Database
1.3.2 GVR'S Internal Database
1.3.3 Secondary Sources & Third-Party Perspectives
1.3.4 Primary Research
1.4 Information Analysis
1.4.1 Data Analysis Models
1.5 Market Formulation & Data Visualization
1.6 Data Validation & Publishing
Chapter 2 Executive Summary & Market Snapshot
2.1 Market Outlook
2.2 Segmental Outlook
2.3 Competitive Insights
Chapter 3 Deep Learnings Industry Outlook, Trends & Scope
3.1 Market Introduction
3.2 Deep Learning-Market Size and Growth Prospects
3.3 Deep Learning -Value Chain Analysis
3.4 Deep Learning -Market Dynamics
3.4.1 MARKET DRIVER ANALYSIS
3.4.1.1 Introduction of new hardware for deep learning applications
3.4.1.2 Improvement in deep learning algorithms
3.4.1.3 Increased penetration in big data analytics
3.4.2 MARKET RESTRAINT ANALYSIS
3.4.2.1 Scalability of deep learning models
3.4.2.2 Requirement of large training datasets for recognition
3.5 Deep Learning-Penetration & Growth Prospect Mapping
3.6 Business Environment Analysis Tools
3.6.1 PEST Analysis
3.6.2 Porter's Five Force Analysis
Chapter 4 Deep Learning Application Solution Outlook
4.1 Market Size Estimates & Forecasts and Trend Analysis, 2017 - 2030 (Revenue, USD Million)
4.2 Deep Learning Market: Solution Movement Analysis
4.2.1 Hardware
4.2.1.1 Market estimates and forecast by region, 2017 - 2030 (USD Million)
4.2.2 Software
4.2.2.1 Market estimates and forecast by region, 2017 - 2030 (USD Million)
4.2.3 Services
4.2.3.1 Market estimates and forecast by region, 2017 - 2030 (USD Million)
4.2.3.2 Installation Services
4.2.3.2.1 Market estimates and forecast by region, 2017 - 2030 (USD Million)
4.2.3.3 Integration Services
4.2.3.3.1 Market estimates and forecast by region, 2017 - 2030 (USD Million)
4.2.3.4 Maintenance & support services
4.2.3.4.1 Market estimates and forecast by region, 2017 - 2030 (USD Million)
Chapter 5 Deep Learning Hardware Outlook
5.1 Market Size Estimates & Forecasts and Trend Analysis, 2017 - 2030 (Revenue, USD Million)
5.2 Deep Learning Market: Hardware Movement Analysis
5.2.1 CPU
5.2.1.1 Market estimates and forecast by region, 2017 - 2030 (USD Million)
5.2.2 GPU
5.2.2.1 Market estimates and forecast by region, 2017 - 2030 (USD Million)
5.2.3 FPGA
5.2.3.1 Market estimates and forecast by region, 2017 - 2030 (USD Million)
5.2.4 ASIC
5.2.4.1 Market estimates and forecast by region, 2017 - 2030 (USD Million)
Chapter 6 Deep Learning Market Application Outlook
6.1 Market Size Estimates & Forecasts and Trend Analysis, 2017 - 2030 (Revenue, USD Million)
6.2 Deep Learning Market: Application Movement Analysis
6.2.1 Image recognition
6.2.1.1 Market estimates and forecast by region, 2017 - 2030 (USD Million)
6.2.2 Voice recognition
6.2.2.1 Market estimates and forecast by region, 2017 - 2030 (USD Million)
6.2.3 Video Surveillance & Diagnostics
6.2.3.1 Market estimates and forecast by region, 2017 - 2030 (USD Million)
6.2.4 Data Mining
6.2.4.1 Market estimates and forecast by region, 2017 - 2030 (USD Million)
Chapter 7 Deep Learning Market End-Use Outlook
7.1 Market Size Estimates & Forecasts and Trend Analysis, 2017 - 2030 (Revenue, USD Million)
7.2 Deep Learning Market: End-Use Movement Analysis
7.2.1 Automotive
7.2.1.1 Market estimates and forecast by region, 2017 - 2030 (USD Million)
7.2.2 Aerospace & Defense
7.2.2.1 Market estimates and forecast by region, 2017 - 2030 (USD Million)
7.2.3 Healthcare
7.2.3.1 Market estimates and forecast by region, 2017 - 2030 (USD Million)
7.2.4 Retail
7.2.4.1 Market estimates and forecast by region, 2017 - 2030 (USD Million)
7.2.5 Others
7.2.5.1 Market estimates and forecast by region, 2017 - 2030 (USD Million)
Chapter 8 Regional Estimates & Trend Analysis
8.1 Market Size Estimates & Forecasts and Trend Analysis, 2017 - 2030 (Revenue, USD Million)
8.2 Deep Learning Market Share by Region, 2022 & 2030
8.3 North America
8.3.1 Market estimates and forecast by solution, 2017 - 2030 (USD Million)
8.3.2 Market estimates and forecast by hardware, 2017 - 2030 (USD Million)
8.3.3 Market estimates and forecast by service, 2017 - 2030 (USD Million)
8.3.4 Market estimates and forecast by application, 2017 - 2030 (USD Million)
8.3.5 Market estimates and forecast by end-use, 2017 - 2030 (USD Million)
8.3.6 U.S.
8.3.6.1 Market estimates and forecast by solution, 2017 - 2030 (USD Million)
8.3.6.2 Market estimates and forecast by hardware, 2017 - 2030 (USD Million)
8.3.6.3 Market estimates and forecast by service, 2017 - 2030 (USD Million)
8.3.6.4 Market estimates and forecast by application, 2017 - 2030 (USD Million)
8.3.6.5 Market estimates and forecast by end-use, 2017 - 2030 (USD Million)
8.3.7 Canada
8.3.7.1 Market estimates and forecast by solution, 2017 - 2030 (USD Million)
8.3.7.2 Market estimates and forecast by hardware, 2017 - 2030 (USD Million)
8.3.7.3 Market estimates and forecast by service, 2017 - 2030 (USD Million)
8.3.7.4 Market estimates and forecast by application, 2017 - 2030 (USD Million)
8.3.7.5 Market estimates and forecast by end-use, 2017 - 2030 (USD Million)
8.3.8 Mexico
8.3.8.1 Market estimates and forecast by solution, 2017 - 2030 (USD Million)
8.3.8.2 Market estimates and forecast by hardware, 2017 - 2030 (USD Million)
8.3.8.3 Market estimates and forecast by service, 2017 - 2030 (USD Million)
8.3.8.4 Market estimates and forecast by application, 2017 - 2030 (USD Million)
8.3.8.5 Market estimates and forecast by end-use, 2017 - 2030 (USD Million)
8.4 Europe
8.4.1 Market estimates and forecast by solution, 2017 - 2030 (USD Million)
8.4.2 Market estimates and forecast by hardware, 2017 - 2030 (USD Million)
8.4.3 Market estimates and forecast by service, 2017 - 2030 (USD Million)
8.4.4 Market estimates and forecast by application, 2017 - 2030 (USD Million)
8.4.5 Market estimates and forecast by end-use, 2017 - 2030 (USD Million)
8.4.6 Germany
8.4.6.1 Market estimates and forecast by solution, 2017 - 2030 (USD Million)
8.4.6.2 Market estimates and forecast by hardware, 2017 - 2030 (USD Million)
8.4.6.3 Market estimates and forecast by service, 2017 - 2030 (USD Million)
8.4.6.4 Market estimates and forecast by application, 2017 - 2030 (USD Million)
8.4.6.5 Market estimates and forecast by end-use, 2017 - 2030 (USD Million)
8.4.7 U.K.
8.4.7.1 Market estimates and forecast by solution, 2017 - 2030 (USD Million)
8.4.7.2 Market estimates and forecast by hardware, 2017 - 2030 (USD Million)
8.4.7.3 Market estimates and forecast by service, 2017 - 2030 (USD Million)
8.4.7.4 Market estimates and forecast by application, 2017 - 2030 (USD Million)
8.4.7.5 Market estimates and forecast by end-use, 2017 - 2030 (USD Million)
8.5 Asia Pacific
8.5.1 Market estimates and forecast by solution, 2017 - 2030 (USD Million)
8.5.2 Market estimates and forecast by hardware, 2017 - 2030 (USD Million)
8.5.3 Market estimates and forecast by service, 2017 - 2030 (USD Million)
8.5.4 Market estimates and forecast by application, 2017 - 2030 (USD Million)
8.5.5 Market estimates and forecast by end-use, 2017 - 2030 (USD Million)
8.5.6 China
8.5.6.1 Market estimates and forecast by solution, 2017 - 2030 (USD Million)
8.5.6.2 Market estimates and forecast by hardware, 2017 - 2030 (USD Million)
8.5.6.3 Market estimates and forecast by service, 2017 - 2030 (USD Million)
8.5.6.4 Market estimates and forecast by application, 2017 - 2030 (USD Million)
8.5.6.5 Market estimates and forecast by end-use, 2017 - 2030 (USD Million)
8.5.7 India
8.5.7.1 Market estimates and forecast by solution, 2017 - 2030 (USD Million)
8.5.7.2 Market estimates and forecast by hardware, 2017 - 2030 (USD Million)
8.5.7.3 Market estimates and forecast by service, 2017 - 2030 (USD Million)
8.5.7.4 Market estimates and forecast by application, 2017 - 2030 (USD Million)
8.5.7.5 Market estimates and forecast by end-use, 2017 - 2030 (USD Million)
8.5.8 Japan
8.5.8.1 Market estimates and forecast by solution, 2017 - 2030 (USD Million)
8.5.8.2 Market estimates and forecast by hardware, 2017 - 2030 (USD Million)
8.5.8.3 Market estimates and forecast by service, 2017 - 2030 (USD Million)
8.5.8.4 Market estimates and forecast by application, 2017 - 2030 (USD Million)
8.5.8.5 Market estimates and forecast by end-use, 2017 - 2030 (USD Million)
8.6 South America
8.6.1 Market estimates and forecast by solution, 2017 - 2030 (USD Million)
8.6.2 Market estimates and forecast by hardware, 2017 - 2030 (USD Million)
8.6.3 Market estimates and forecast by service, 2017 - 2030 (USD Million)
8.6.4 Market estimates and forecast by application, 2017 - 2030 (USD Million)
8.6.5 Market estimates and forecast by end-use, 2017 - 2030 (USD Million)
8.6.6 Brazil
8.6.6.1 Market estimates and forecast by solution, 2017 - 2030 (USD Million)
8.6.6.2 Market estimates and forecast by hardware, 2017 - 2030 (USD Million)
8.6.6.3 Market estimates and forecast by service, 2017 - 2030 (USD Million)
8.6.6.4 Market estimates and forecast by application, 2017 - 2030 (USD Million)
8.6.6.5 Market estimates and forecast by end-use, 2017 - 2030 (USD Million)
8.7 MEA
8.7.1 Market estimates and forecast by solution, 2017 - 2030 (USD Million)
8.7.2 Market estimates and forecast by hardware, 2017 - 2030 (USD Million)
8.7.3 Market estimates and forecast by service, 2017 - 2030 (USD Million)
8.7.4 Market estimates and forecast by application, 2017 - 2030 (USD Million)
8.7.5 Market estimates and forecast by end-use, 2017 - 2030 (USD Million)
Chapter 9 Competitive Analysis
9.1 Key Global Players, Recent Developments & Their Impact on the Industry
9.2 Key Company Categorization (Key innovators, Market leaders, and Emerging players)
9.3 Key Company Analysis, 2022
Chapter 10 Competitive Landscape
10.1 Advanced Micro Devices, Inc.
10.1.1 Company overview
10.1.2 Financial performance
10.1.3 Product benchmarking
10.1.4 Recent developments
10.2 ARM Ltd.
10.2.1 Company Overview
10.2.2 Financial performance
10.2.3 Product benchmarking
10.2.4 Recent developments
10.3 Clarifai, Inc.
10.3.1 Company overview
10.3.2 Financial performance
10.3.3 Product benchmarking
10.3.4 Recent developments
10.4 Entilic
10.4.1 Company overview
10.4.2 Financial performance
10.4.3 Product benchmarking
10.4.4 Recent developments
10.5 Google, Inc.
10.5.1 Company overview
10.5.2 Financial performance
10.5.3 Product benchmarking
10.5.4 Recent developments
10.6 HyperVerge
10.6.1 Company overview
10.6.2 Financial performance
10.6.3 Product benchmarking
10.6.4 Recent developments
10.7 IBM Corporation
10.7.1 Company overview
10.7.2 Financial performance
10.7.3 Product benchmarking
10.7.4 Recent developments
10.8 Intel Corporation
10.8.1 Company overview
10.8.2 Financial performance
10.8.2 Product benchmarking
10.8.3 Recent developments
10.9 Microsoft Corporation
10.9.1 Company overview
10.9.2 Financial performance
10.9.3 Product benchmarking
10.9.4 Recent developments
10.10 NVIDIA Corporation
10.10.1 Company overview
10.10.2 Financial performance
10.10.3 Product benchmarking
10.10.4 Recent developments
List of Tables
Table 1 Global deep learning market, 2017 - 2030 (USD Million)
TABLE 2 Global market estimates and forecasts by region, 2017 - 2030 (USD Million)
TABLE 3 Global market estimates and forecasts by solution, 2017 - 2030 (USD Million)
TABLE 4 Global market estimates and forecasts by hardware, 2017 - 2030 (USD Million)
TABLE 5 Global market estimates and forecasts by services, 2017 - 2030 (USD Million)
TABLE 6 Global market estimates and forecasts by application, 2017 - 2030 (USD Million)
TABLE 7 Global market estimates and forecasts by end-use, 2017 - 2030 (USD Million)
TABLE 8 Global deep learning-based hardware market by region, 2017 - 2030 (USD Million)
TABLE 9 Global deep learning-based software market by region, 2017 - 2030 (USD Million)
TABLE 10 Global deep learning-based services market by region, 2017 - 2030 (USD Million)
TABLE 11 Global deep learning-based installation services market by region, 2017 - 2030 (USD Million)
TABLE 12 Global deep learning-based integration services market by region, 2017 - 2030 (USD Million)
TABLE 13 Global deep learning-based maintenance & support services market by region, 2017 - 2030 (USD Million)
TABLE 14 Global deep learning-based CPU market by region, 2017 - 2030 (USD Million)
TABLE 15 Global deep learning-based GPU market by region, 2017 - 2030 (USD Million)
TABLE 16 Global deep learning-based FPGA market by region, 2017 - 2030 (USD Million)
TABLE 17 Global deep learning-based ASIC market by region, 2017 - 2030 (USD Million)
TABLE 18 Global deep learning market in image recognition application by region, 2017 - 2030 (USD Million)
TABLE 19 Global deep learning market in voice recognition application by region, 2017 - 2030 (USD Million)
TABLE 20 Global deep learning market in video surveillance & diagnostics application by region, 2017 - 2030 (USD Million)
TABLE 21 Global deep learning market in data mining application by region, 2017 - 2030 (USD Million)
TABLE 22 Global deep learning market in automotive application by region, 2017 - 2030 (USD Million)
TABLE 23 Global deep learning market in aerospace & defense application by region, 2017 - 2030 (USD Million)
TABLE 24 Global deep learning market in healthcare application by region, 2017 - 2030 (USD Million)
TABLE 25 Global deep learning market in retail application by region, 2017 - 2030 (USD Million)
TABLE 26 Global deep learning market in other applications by region, 2017 - 2030 (USD Million)
TABLE 27 North America Deep Learning Market, by Solution, 2017 - 2030 (USD Million)
TABLE 28 North America Deep Learning Market, by Hardware, 2017 - 2030 (USD Million)
TABLE 29 North America deep learning market by services, 2017 - 2030 (USD Million)
TABLE 30 North America Deep Learning Market, by Application, 2017 - 2030 (USD Million)
TABLE 31 North America Deep Learning Market, by End-Use, 2017 - 2030 (USD Million)
TABLE 32 U.S. Deep Learning Market, by Solution, 2017 - 2030 (USD Million)
TABLE 33 U.S. Deep Learning Market, by Hardware, 2017 - 2030 (USD Million)
TABLE 34 U.S. deep learning market by services, 2017 - 2030 (USD Million)
TABLE 35 U.S. Deep Learning Market, by Application, 2017 - 2030 (USD Million)
TABLE 36 U.S. Deep Learning Market, by End-Use, 2017 - 2030 (USD Million)
TABLE 37 Canada Deep Learning Market, by Solution, 2017 - 2030 (USD Million)
TABLE 38 Canada Deep Learning Market, by Hardware, 2017 - 2030 (USD Million)
TABLE 39 Canada deep learning market by services, 2017 - 2030 (USD Million)
TABLE 40 Canada Deep Learning Market, by Application, 2017 - 2030 (USD Million)
TABLE 41 Canada deep learning market by end-use, 2017 - 2030 (USD Million)
TABLE 42 Europe Deep Learning Market, by Solution, 2017 - 2030 (USD Million)
TABLE 43 Europe Deep Learning Market, by Hardware, 2017 - 2030 (USD Million)
TABLE 44 Europe deep learning market by services, 2017 - 2030 (USD Million)
TABLE 45 Europe Deep Learning Market, by Application, 2017 - 2030 (USD Million)
TABLE 46 Europe deep learning market by end-use, 2017 - 2030 (USD Million)
TABLE 47 Germany Deep Learning Market, by Solution, 2017 - 2030 (USD Million)
TABLE 48 Germany Deep Learning Market, by Hardware, 2017 - 2030 (USD Million)
TABLE 49 Germany deep learning market by services, 2017 - 2030 (USD Million)
TABLE 50 Germany Deep Learning Market, by Application, 2017 - 2030 (USD Million)
TABLE 51 Germany deep learning market by end-use, 2017 - 2030 (USD Million)
TABLE 52 U.K. Deep Learning Market, by Solution, 2017 - 2030 (USD Million)
TABLE 53 U.K. Deep Learning Market, by Hardware, 2017 - 2030 (USD Million)
TABLE 54 U.K. deep learning market by services, 2017 - 2030 (USD Million)
TABLE 55 U.K. Deep Learning Market, by Application, 2017 - 2030 (USD Million)
TABLE 56 U.K. deep learning market by end-use, 2017 - 2030 (USD Million)
TABLE 57 Asia Pacific Deep Learning Market, by Solution, 2017 - 2030 (USD Million)
TABLE 58 Asia Pacific Deep Learning Market, by Hardware, 2017 - 2030 (USD Million)
TABLE 59 Asia Pacific deep learning market by services, 2017 - 2030 (USD Million)
TABLE 60 Asia Pacific Deep Learning Market, by Application, 2017 - 2030 (USD Million)
TABLE 61 Asia Pacific deep learning market by end-use, 2017 - 2030 (USD Million)
TABLE 62 China Deep Learning Market, by Solution, 2017 - 2030 (USD Million)
TABLE 63 China Deep Learning Market, by Hardware, 2017 - 2030 (USD Million)
TABLE 64 China deep learning market by services, 2017 - 2030 (USD Million)
TABLE 65 China Deep Learning Market, by Application, 2017 - 2030 (USD Million)
TABLE 66 China deep learning market by end-use, 2017 - 2030 (USD Million)
TABLE 67 India Deep Learning Market, by Solution, 2017 - 2030 (USD Million)
TABLE 68 India Deep Learning Market, by Hardware, 2017 - 2030 (USD Million)
TABLE 69 India deep learning market by services, 2017 - 2030 (USD Million)
TABLE 70 India Deep Learning Market, by Application, 2017 - 2030 (USD Million)
TABLE 71 India deep learning market by end-use, 2017 - 2030 (USD Million)
TABLE 72 Japan Deep Learning Market, by Solution, 2017 - 2030 (USD Million)
TABLE 73 Japan Deep Learning Market, by Hardware, 2017 - 2030 (USD Million)
TABLE 74 Japan deep learning market by services, 2017 - 2030 (USD Million)
TABLE 75 Japan Deep Learning Market, by Application, 2017 - 2030 (USD Million)
TABLE 76 Japan deep learning market by end-use, 2017 - 2030 (USD Million)
TABLE 77 South America Deep Learning Market, by Solution, 2017 - 2030 (USD Million)
TABLE 78 South America Deep Learning Market, by Hardware, 2017 - 2030 (USD Million)
TABLE 79 South America deep learning market by services, 2017 - 2030 (USD Million)
TABLE 80 South America Deep Learning Market, by Application, 2017 - 2030 (USD million)
TABLE 81 South America deep learning market by end-use, 2017 - 2030 (USD Million)
TABLE 82 Brazil Deep Learning Market, by Solution, 2017 - 2030 (USD Million)
TABLE 83 Brazil Deep Learning Market, by Hardware,2017 - 2030 (USD Million)
TABLE 84 Brazil deep learning market by services,2017 - 2030 (USD Million)
TABLE 85 Brazil Deep Learning Market, by Application,2017 - 2030 (USD Million)
TABLE 86 Brazil deep learning market by end-use,2017 - 2030 (USD Million)
TABLE 87 Mexico Deep Learning Market, by Solution, 2017 - 2030 (USD Million)
TABLE 88 Mexico Deep Learning Market, by Hardware, 2017 - 2030 (USD Million)
TABLE 89 Mexico deep learning market by services, 2017 - 2030 (USD Million)
TABLE 90 Mexico Deep Learning Market, by Application, 2017 - 2030 (USD Million)
TABLE 91 Mexico deep learning market by end-use, 2017 - 2030 (USD Million)
TABLE 92 MEA Deep Learning Market, by Solution 2017 - 2030 (USD Million)
TABLE 93 MEA Deep Learning Market, by Hardware, 2017 - 2030 (USD Million)
TABLE 94 MEA deep learning market by services 2017 - 2030 (USD Million)
TABLE 95 MEA Deep Learning Market, by Application, 2017 - 2030 (USD Million)
TABLE 96 MEA deep learning market by end-use, 2017 - 2030 (USD Million)
List of Figures
Fig 1 Deep learning market segmentation and scope
FIG. 2 Information procurement
FIG. 3 Primary research pattern
FIG. 4 Primary research process
FIG. 5 Market formulation and data visualization
FIG. 6 Industry Snapshot - Deep Learning
FIG. 7 Big data revenue, 2017 - 2030 (USD Million)
FIG. 8 Penetration & growth prospect mapping
FIG. 9 Porter’s five forces analysis
FIG. 10 Deep learning - PEST analysis
FIG. 11 Deep learning market solution outlook key takeaways
FIG. 12 Deep learning market: Solution movement analysis
FIG. 13 Global deep learning-based hardware market, 2017 - 2030 (USD Million)
FIG. 14 Global deep learning-based software market, 2017 - 2030 (USD Million)
FIG. 15 Global deep learning-based services market, 2017 - 2030 (USD Million)
FIG. 16 Global deep learning-based installation services market, 2017 - 2030 (USD Million)
FIG. 17 Global deep learning-based integration services market, 2017 - 2030 (USD Million)
FIG. 18 Global deep learning-based maintenance & support services market, 2017 - 2030 (USD Million)
FIG. 19 Deep learning market hardware outlook key takeaways
FIG. 20 Deep learning market: Hardware movement analysis
FIG. 21 Global deep learning-based CPU market, 2017 - 2030 (USD Million)
FIG. 22 Global deep learning-based GPU market, 2017 - 2030 (USD Million)
FIG. 23 Global deep learning-based FPGA market, 2017 - 2030 (USD Million)
FIG. 24 Global deep learning-based ASIC market, 2017 - 2030 (USD Million)
FIG. 25 Deep learning market application outlook key takeaways
FIG. 26 Deep learning market: Application movement analysis
FIG. 27 Global deep learning market in image recognition application, 2017 - 2030 (USD Million)
FIG. 28 Global deep learning market in voice recognition application, 2017 - 2030 (USD Million)
FIG. 29 Global deep learning market in video surveillance & diagnostics application, 2017 - 2030 (USD Million)
FIG. 30 Global deep learning market in data mining application, 2017 - 2030 (USD Million)
FIG. 31 Deep learning market end-use outlook key takeaways
FIG. 32 Deep learning market: End-use movement analysis
FIG. 33 Global deep learning market in automotive application, 2017 - 2030 (USD Million)
FIG. 34 Global deep learning market in aerospace & defense application, 2017 - 2030 (USD Million)
FIG. 35 Global deep learning market in healthcare application, 2017 - 2030 (USD Million)
FIG. 36 Global deep learning market in retail application, 2017 - 2030 (USD Million)
FIG. 37 Global deep learning market in other applications, 2017 - 2030 (USD Million)
FIG. 38 Regional market place: Key takeaways
FIG. 39 Regional outlook, 2022 & 2030
FIG. 40 North America deep learning market, 2017 - 2030 (USD Million)
FIG. 41 Europe deep learning market, 2017 - 2030 (USD Million)
FIG. 42 Asia Pacific deep learning market, 2017 - 2030 (USD Million)
FIG. 43 Asia Pacific deep learning market, 2017 - 2030 (USD Million)
Companies Mentioned
- Advanced Micro Devices, Inc.
- Arm Ltd.
- Clarifai, Inc.
- Entilic
- Google, Inc.
- Hyperverge
- IBM Corporation
- Intel Corporation
- Microsoft Corporation
- Nvidia Corporation
Methodology
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Table Information
| Report Attribute | Details |
|---|---|
| No. of Pages | 118 |
| Published | February 2023 |
| Forecast Period | 2022 - 2030 |
| Estimated Market Value ( USD | $ 49.6 Billion |
| Forecasted Market Value ( USD | $ 526.7 Billion |
| Compound Annual Growth Rate | 33.5% |
| Regions Covered | Global |
| No. of Companies Mentioned | 10 |
