Global Deep Learning Market: Drivers, Restraints, Opportunities, Trends, and Forecasts to 2023

  • Product Code:
    RP-ID-10078072
  • Published Date:
    Mar 2019
  • Region:
    Global
  • Pages:
    106
  • Category:
    ICT & Telecom
  • Publisher:
    Infoholic Research
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.

Table of Contents
1 Industry Outlook 10
1.1. Industry Overview 10
1.2. Industry Trends 11
1.3. PEST Analysis 13
2 Report Outline 14
2.1 Report Scope 14
2.2 Report Summary 14
2.3 Research Methodology 16
2.4 Report Assumptions 16
3 Market Snapshot 17
3.1 Total Addressable Market 17
3.2 Segmented Addressable Market 17
3.3 Related Markets 18
3.3.1 Machine Learning Market 18
3.3.2 Artificial Intelligence Market 18
4 Market Outlook 19
4.1 Overview 19
4.2 Regulatory Bodies and Standards 20
4.3 Porter 5 (Five) Forces 21
5 Market Characteristics 22
5.1 Neural Network diagram 22
5.2 Use Cases of Deep Learning 23
5.3 Market Segmentation 24
5.4 Market Dynamics 24
5.4.1 Drivers 25
5.4.1.1 Faster Processor Performance 25
5.4.1.2 Large training data size 26
5.4.1.3 Sophisticated neural nets 26
5.4.2 Restraints 26
5.4.2.1 Implementation challenges 26
5.4.2.2 Rigid business models 26
5.4.2.3 Dearth of skilled data scientists 27
5.4.2.4 Affordability of organizations 27
5.4.2.5 Data security concerns and data inaccessibility 27
5.4.3 Opportunities 27
5.4.3.1 Development in Big Data Technologies 27
5.4.3.2 Expanding End-user Base 28
5.4.3.3 Extensive R&D 28
5.5 DRO – Impact Analysis 29
6 Trends, Roadmap, and Projects 30
6.1 Market Trends & Impact 30
6.2 Technology Roadmap 31
7 Geographic Segmentation: Market Size and Analysis 32
7.1 Overview 32
7.1.1 North America 33
7.1.2 US 34
7.1.3 Canada 34
7.2 EMEA 34
7.2.1 The UK 35
7.2.2 Germany 35
7.3 Asia Pacific 36
7.3.1 India 36
7.3.2 China 37
7.3.3 Japan 37
7.4 Latin America 38
8 Deep Learning Market by Solutions 39
8.1 Software Solutions 40
8.2 Hardware 40
9 Global Deep Learning Market by Applications 42
9.1 Image Recognition 43
9.2 Voice Recognition 43
9.3 Video Surveillance and Diagnostics 44
9.4 Data Mining 45
9.5 Others 45
10 Global Deep Learning Market by End-users 47
10.1 Medical 48
10.2 Automotive 49
10.3 Retail 50
10.4 Finance 50
10.5 IT & Telecommunication 51
10.6 Industrial 52
10.7 Aerospace and Defence 53
10.8 Media and Advertising 54
10.9 Oil, Gas and Energy 54
10.10 Others 55
11 Vendors Profiles 57
11.1 Microsoft Corporation 57
11.1.1 Overview 57
11.1.2 Business Units 58
11.1.3 Microsoft Corporation in Deep Learning 60
11.1.4 Business Focus 60
11.1.5 SWOT Analysis 61
11.1.6 Business Strategies 61
11.2 IBM Corporation 62
11.2.1 Overview 62
11.2.2 Business Units 63
11.2.3 Geographic Revenue 66
11.2.4 IBM Corporation in Deep Learning 66
11.2.5 Business Focus 67
11.2.6 SWOT Analysis 67
11.2.7 Business Strategies 68
11.3 Amazon Web Services 68
11.3.1 Overview 68
11.3.2 Business Units 69
11.3.3 Geographic Revenue 70
11.3.4 Amazon Web Services in Deep Learning 71
11.3.5 Business Focus 71
11.3.6 SWOT Analysis 72
11.3.7 Business Strategies 72
11.4 Google Inc. 73
11.4.1 Overview 73
11.4.2 Business Units 74
11.4.3 Geographic Revenue 75
11.4.4 Google Inc. in Deep Learning 76
11.4.5 Business Focus 76
11.4.6 SWOT Analysis 77
11.4.7 Business Strategies 77
11.5 Nvidia Corporation 78
11.5.1 Overview 79
11.5.2 Business Units 79
11.5.3 Geographic Revenue 80
11.5.4 Nvidia in Deep Learning 81
11.5.5 Business Focus 81
11.5.6 SWOT Analysis 82
11.5.7 Business Strategies 82
11.6 Hewlett-Packard Development Company, L.P. 83
11.6.1 Overview 83
11.6.2 Business Segments 85
11.6.3 Geographic Revenue 86
11.6.4 HP in Deep Learning 86
11.6.5 Business Focus 87
11.6.6 SWOT Analysis 87
11.6.7 Business Strategies 88
11.7 Baidu Inc. 88
11.7.1 Overview 88
11.7.2 Business Segments 89
11.7.3 Geographic Revenue 90
11.7.4 Baidu Inc. in Deep Learning 91
11.7.5 Business Focus 92
11.7.6 SWOT Analysis 93
11.7.7 Business Strategies 93
11.8 Intel Corporation 94
11.8.1 Overview 94
11.8.2 Business Segments 95
11.8.3 Geographic Revenue 97
11.8.4 Intel Corporation in Deep Learning 97
11.8.5 Business Focus 98
11.8.6 SWOT Analysis 98
11.8.7 Business Strategies 98
12 Companies to Watch for 100
12.1 Deepmind Technologies Ltd. (Acquired by Google) 100
12.1.1 Overview 100
12.1.2 Deepmind Offerings 100
12.2 Deep Vision 100
12.2.1 Overview 100
12.2.2 Deep Vision Offerings 101
12.3 Bay Labs 101
12.3.1 Bay Labs Offerings 101
Abbreviations 102

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Microsoft Corporation,IBM Corporation,Amazon Web Services,Nvidia Corporation,Deepmind Technologies Ltd
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