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

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


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

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



Executive Summary

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

 

To know more information on Purchase by Section, please send a mail to sales@kenresearch.com

Charts

 

CHART 1 PEST ANALYSIS OF GLOBAL DEEP LEARNING MARKET 13

CHART 2 RESEARCH METHODOLOGY OF GLOBAL DEEP LEARNING MARKET 16

CHART 3 GLOBAL DEEP LEARNING MARKET REVENUE, 2017-2023 (USD BILLION) 17

CHART 4 PORTER 5 FORCES ON GLOBAL DEEP LEARNING MARKET 21

CHART 5 NEURAL NETWORK DIAGRAM 22

CHART 6 GLOBAL DEEP LEARNING MARKET SEGMENTATION 24

CHART 7 MARKET DYNAMICS-DRIVERS, RESTRAINTS & OPPORTUNITIES 25

CHART 8 DRO-IMPACT ANALYSIS OF GLOBAL DEEP LEARNING MARKET 29

CHART 9 TECHNOLOGY ROADMAP FOR GLOBAL DEEP LEARNING MARKET 31

CHART 10 GLOBAL DEEP LEARNING MARKET SHARE BY GEOGRAPHIES, 2017 AND 2023 32

CHART 11 DEEP LEARNING MARKET REVENUE IN NORTH AMERICA, 2017-2023 (USD MILLION) 33

CHART 12 DEEP LEARNING MARKET REVENUE IN EMEA, 2017-2023 (USD MILLION) 36

CHART 13 DEEP LEARNING MARKET REVENUE IN ASIA PACIFIC, 2017-2023 (USD MILLION) 37

CHART 14 DEEP LEARNING MARKET REVENUE IN LATIN AMERICA, 2017-2023 (USD MILLION) 38

CHART 15 DEEP LEARNING MARKET REVENUE BY SOLUTIONS (USD MILLION) 39

CHART 16 GLOBAL DEEP LEARNING MARKET REVENUE BY SOFTWARE SOLUTIONS (USD MILLION) 40

CHART 17 GLOBAL DEEP LEARNING MARKET REVENUE BY HARDWARE SOLUTIONS (USD MILLION) 40

CHART 18 GLOBAL DEEP LEARNING MARKET REVENUE BY APPLICATIONS, 2017-2023 (USD MILLION) 42

CHART 19 GLOBAL DEEP LEARNING MARKET REVENUE BY IMAGE RECOGNITION, 2017-2023 (USD MILLION) 43

CHART 20 GLOBAL DEEP LEARNING MARKET REVENUE BY VOICE RECOGNITION, 2017-2023 (USD MILLION) 43

CHART 21 GLOBAL DEEP LEARNING MARKET REVENUE BY VIEO SURVEILLANCE AND DIAGNOSTICS, 2017-2023 (USD MILLION) 44

CHART 22 GLOBAL DEEP LEARNING MARKET REVENUE BY DATA MINING, 2017-2023 (USD MILLION) 45

CHART 23 GLOBAL DEEP LEARNING MARKET REVENUE BY OTHERS, 2017-2023 (USD MILLION) 45

CHART 24 GLOBAL DEEP LEARNING MARKET REVENUE BY END-USERS, 2017-2023 (USD MILLION) 48

CHART 25 GLOBAL DEEP LEARNING MARKET REVENUE BY MEDICAL, 2017-2023 (USD MILLION) 48

CHART 26 GLOBAL DEEP LEARNING MARKET REVENUE BY AUTOMOTIVE, 2017-2023 (USD MILLION) 49

CHART 27 GLOBAL DEEP LEARNING MARKET REVENUE BY RETAIL, 2017-2023 (USD MILLION) 50

CHART 28 GLOBAL DEEP LEARNING MARKET REVENUE BY FINANCE, 2017-2023 (USD MILLION) 50

CHART 29 GLOBAL DEEP LEARNING MARKET REVENUE BY IT & TELECOMMUNICATION, 2017-2023 (USD MILLION) 51

CHART 30 GLOBAL DEEP LEARNING MARKET REVENUE BY INDUSTRIAL, 2017-2023 (USD MILLION) 52

CHART 31 GLOBAL DEEP LEARNING MARKET REVENUE BY AEROSPACE AND DEFENCE, 2017-2023 (USD MILLION) 53

CHART 32 GLOBAL DEEP LEARNING MARKET REVENUE BY MEDIA AND ADVERTISING, 2017-2023 (USD MILLION) 54

CHART 33 GLOBAL DEEP LEARNING MARKET REVENUE BY OIL, GAS AND ENERGY, 2017-2023 (USD MILLION) 54

CHART 34 GLOBAL DEEP LEARNING MARKET REVENUE BY OTHERS, 2017-2023 (USD MILLION) 55

CHART 35 MICROSOFT CORPORATION: OVERVIEW SNAPSHOT 58

CHART 36 MICROSOFT CORPORATION: BUSINESS UNITS 59

CHART 37 MICROSOFT CORPORATION: SWOT ANALYSIS 61

CHART 38 IBM CORPORATION: OVERVIEW SNAPSHOT 63

CHART 39 IBM CORPORATION: BUSINESS UNITS 65

CHART 40 IBM CORPORATION: GEOGRAPHIC REVENUE 66

CHART 41 IBM CORPORATION: SWOT ANALYSIS 67

CHART 42 AMAZON WEB SERVICES: OVERVIEW SNAPSHOT 69

CHART 43 AMAZON WEB SERVICES: BUSINESS UNITS 70

CHART 44 AMAZON WEB SERVICES: GEOGRAPHIC REVENUE 70

CHART 45 AMAZON WEB SERVICES: SWOT ANALYSIS 72

CHART 46 GOOGLE INC.: OVERVIEW SNAPSHOT 74

CHART 47 GOOGLE INC.: BUSINESS UNITS 75

CHART 48 GOOGLE INC.: GEOGRAPHIC REVENUE 75

CHART 49 GOOGLE INC.: SWOT ANALYSIS 77

CHART 50 HP: OVERVIEW SNAPSHOT 84

CHART 51 HP: BUSINESS SEGMENTS 85

CHART 52 HP: REVENUE BY GEOGRAPHIES 86

CHART 53 HP: SWOT ANALYSIS 87

 

Tables

 

TABLE 1 GLOBAL DEEP LEARNING MARKET REVENUE BY REGIONS, 2017-2023 (USD MILLION) 32

TABLE 2 GLOBAL DEEP LEARNING MARKET REVENUE BY SOLUTIONS, 2017-2023 (USD MILLION) 39

TABLE 3 GLOBAL DEEP LEARNING MARKET REVENUE BY APPLICATIONS, 2017-2023 (USD MILLION) 42

TABLE 4 GLOBAL DEEP LEARNING MARKET REVENUE BY END-USERS, 2017-2023 (USD MILLION) 47

 

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


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