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Deep Learning Market by Application (Speech Recognition, Image Recognition, Data Mining, Drug Discovery, Driver Assistance, and Others), by Components (Hardware and Software), by Architecture (Recurrent Neural Networks (RNN), Convolutional Neural Networks (CNN), Deep Belief Networks (DBN), Deep Stacking Networks (DSN), and Graphical Processing Units (GRU)), and by End-use Industry (Automotive, Healthcare, Media & Entertainment, BFSI, Others): Global Industry Perspective, Comprehensive Analysis and Forecast, 2017 – 2024

Published Date: 02-Aug-2018 Category: Technology & Media Report Format : PDF Pages: 110 Report Code: ZMR-1646 Status : Published

Global deep learning market expected to reach USD 23.6 billion globally by 2024, growing at a CAGR of around 39% between 2018 and 2024. Deep learning is a tool used in machine learning that engages artificial neural networks with several layers each having a high degree of functionality.

Description

The report analyzes and forecasts the deep learning market on a global and regional level. The study offers past data from 2015 to 2017 along with forecast from 2018 to 2024 based on revenue (USD Billion). Assessment of deep learning market dynamics gives a brief thought about the drivers and restraints for the deep learning market along with the impact they have on the demand over the years to come. Additionally, the report also includes the study of opportunities available in the deep learning market on a global level.

The report gives a transparent view of the deep learning market. We have included a detailed competitive scenario and portfolio of leading vendors operative in the deep learning market. To understand the competitive landscape in the deep learning market, an analysis of Porter’s Five Forces model for the deep learning market has also been included. The report also covers patent analysis with bifurcation into a patent trend, patent by the company, and patent by region. The study encompasses a market attractiveness analysis, wherein components, type, end-user industry, and regional segments are benchmarked based on their market size, growth rate, and general attractiveness.

Global Deep Learning Market

The study provides a crucial view of the deep learning by segmenting the market based on application, component, architecture, end-use industry, and region. All the segments of deep learning market have been analyzed based on present and future trends and the market is estimated from 2018 to 2024. Based on application, global deep learning market is categorized into speech recognition, image recognition, data mining, drug discovery, driver assistance, and others. Hardware and software are included in the components segment of global deep learning market. Recurrent Neural Networks (RNN), Convolutional Neural Networks (CNN), Deep Belief Networks (DBN), Deep Stacking Networks (DSN), Graphical Processing Units (GRU) is the architecture segment for deep learning market. Automotive, healthcare, media & entertainment, BFSI, and others are included in the end-user industry. The regional segmentation comprises the current and forecast demand for the Middle East & Africa, North America, Asia Pacific, Latin America, and Europe for deep learning market with further segmentation into the U.S., Canada, Mexico, the UK, France, Germany, China, Japan, India, Brazil, and Argentina, among others are included in the report.

The competitive profiling of market players of deep learning market includes company and financial overview, business strategies adopted by them, their recent developments, and products offered by them which can help in assessing competition in the market. Market players included in the report are IBM Corporation, Intel Corporation, NVIDIA Corporation, Alphabet Inc., Advanced Micro Devices Inc., Microsoft Corporation, Arm Holdings, Qualcomm Technologies Inc., Micron Technology Inc., and Amazon Web Services, among others.

The report segments the global deep learning market as follows:

Global Deep Learning Market: Application Segment Analysis

  • Speech Recognition
  • Image Recognition
  • Data Mining
  • Drug Discovery
  • Driver Assistance
  • Others

Global Deep Learning Market: Component Segment Analysis

  • Hardware
  • Software

Global Deep Learning Market: Architecture Industry Segment Analysis

  • RNN
  • CNN
  • DBN
  • DSN
  • GRU

Global Deep Learning Market: End-use Industry Segment Analysis

  • Automotive
  • Healthcare
  • Media & Entertainment
  • BFSI
  • Others

Global Deep Learning Market: Regional Segment Analysis

  • North America
    • The U.S.
  • Europe
    • UK
    • France
    • Germany
  • Asia Pacific
    • China
    • Japan
    • India
  • Latin America
    • Brazil
  • Middle East and Africa

Table Of Content

  • Chapter 1. Preface
    • 1.1. Report Description
      • 1.1.1. Objective
      • 1.1.2. Target Audience
      • 1.1.3. Unique Selling Proposition (USP) & Offerings
    • 1.2. Research Scope
    • 1.3. Research Methodology
      • 1.3.1. Market Research Process
      • 1.3.2. Market Research Methodology
      • 1.3.3. Level 1: Primary Research
      • 1.3.4. Level 2: Secondary Research
      • 1.3.5. Level 3: Data Validation and Expert Panel Assessment Report Description and Scope
  •  
  • Chapter 2. Executive Summary
    • 2.1. Global Deep Learning Market, 2015-2024, (USD Billion)
    • 2.2. Deep Learning Market: Market Snapshot
  •  
  • Chapter 3. Global Deep Learning Market - Industry Analysis
    • 3.1. Introduction
    • 3.2. Industry ecosystem analysis
    • 3.3. Technology landscape
    • 3.4. Market Drivers
      • 3.4.1. North America
        • 3.4.1.1. Government initiatives to use deep learning in defense applications
      • 3.4.2. Europe
      • 3.4.3. Asia Pacific
      • 3.4.4. Latin America
      • 3.4.5. MEA
    • 3.5. Restraints
      • 3.5.1. High initial investments
    • 3.6. Opportunity
      • 3.6.1. Introduction of autonomous vehicles
    • 3.7. Innovation & sustainability
    • 3.8. Regulatory landscape
    • 3.9. Porter's Five Forces Analysis
    • 3.10. PESTLE Analysis
    • 3.11. Smart Speaker Market: Market Attractiveness Analysis
      • 3.11.1. Market Attractiveness Analysis by Application Segment
      • 3.11.2. Market Attractiveness Analysis by Component Segment.
      • 3.11.3. Market Attractiveness Analysis by Architecture Segment
      • 3.11.4. Market Attractiveness Analysis by End-Use Industry Segment
      • 3.11.5. Market Attractiveness Analysis by Regional Segment
  •  
  • Chapter 4. Global Deep Learning Market - Competitive Landscape
    • 4.1. Company Market Share Analysis, 2017 (Subject to Data Availability)
    • 4.2. Strategic Development
      • 4.2.1. Acquisitions and Mergers
      • 4.2.2. New Product Launch
      • 4.2.3. Agreements, Partnerships, Collaborations and Joint Ventures
      • 4.2.4. Research and Development, Product and Regional Expansion
    • 4.3. Product Portfolio
    • 4.4. Patent Analysis (2012-2017)
      • 4.4.1. Patent Trend
      • 4.4.2. Patent Share by Company
      • 4.4.3. By Region
  •  
  • Chapter 5. Deep Learning Market - Application Segment Analysis
    • 5.1. Global Deep Learning Market Revenue Share, by Application, 2017 & 2024
    • 5.2. Global Deep Learning Market by Speech Recognition, 2015 - 2024 (USD Billion)
    • 5.3. Global Deep Learning Market by Image Recognition, 2015 - 2024 (USD Billion)
    • 5.4. Global Deep Learning Market by Data Mining, 2015 - 2024 (USD Billion)
    • 5.5. Global Deep Learning Market by Drug Discovery, 2015 - 2024 (USD Billion)
    • 5.6. Global Deep Learning Market by Driver Assistance, 2015 - 2024 (USD Billion)
    • 5.7. Global Deep Learning Market by Others, 2015 - 2024 (USD Billion)
  •  
  • Chapter 6. Deep Learning Market - Component Segment Analysis
    • 6.1. Global Deep Learning Market Revenue Share, by Components, 2017 & 2024
    • 6.2. Global Deep Learning Market by Hardware, 2015 - 2024 (USD Billion)
    • 6.3. Global Deep Learning Market by Software, 2015 - 2024 (USD Billion)
  •  
  • Chapter 7. Deep Learning Market - Architecture Segment Analysis
    • 7.1. Global Deep Learning Market Revenue Share, by Architecture, 2017 & 2024
    • 7.2. Global Deep Learning Market by RNN, 2015 - 2024 (USD Billion)
    • 7.3. Global Deep Learning Market by CNN, 2015 - 2024 (USD Billion)
    • 7.4. Global Deep Learning Market by DBN, 2015 - 2024 (USD Billion)
    • 7.5. Global Deep Learning Market by DSN, 2015 - 2024 (USD Billion)
    • 7.6. Global Deep Learning Market by GRU, 2015 - 2024 (USD Billion)
  •  
  • Chapter 8. Global Deep Learning Market - End-User Industry Segment Analysis
    • 8.1. Global Deep Learning Market Revenue Share, by End-Use Industry 2017 & 2024
    • 8.2. Global Deep Learning Market for Automotive, 2015 - 2024 (USD Billion)
    • 8.3. Global Deep Learning Market for Healthcare, 2015 - 2024 (USD Billion)
    • 8.4. Global Deep Learning Market for Media & Entertainment, 2015 - 2024 (USD Billion)
    • 8.5. Global Deep Learning Market for BFSI, 2015 - 2024 (USD Billion)
    • 8.6. Global Deep Learning Market for Others, 2015 - 2024 (USD Billion)
  •  
  • Chapter 9. Deep Learning Market - Regional Analysis
    • 9.1. Global Deep Learning Market: Regional Overview
      • 9.1.1. Global Deep Learning Market Revenue Share, By Region, 2017 And 2024
    • 9.2. North America
      • 9.2.1. North America Deep Learning Market Revenue, 2015 - 2024 (USD Billion)
      • 9.2.2. North America Deep Learning Market Revenue, By Application, 2015 - 2024 (USD Billion)
      • 9.2.3. North America Deep Learning Market Revenue, By Component, 2015 - 2024 (USD Billion)
      • 9.2.4. North America Deep Learning Market Revenue, By Architecture Industry, 2015 - 2024 (USD Billion)
      • 9.2.5. North America Deep Learning Market Revenue, By End-User Industry, 2015 - 2024 (USD Billion)
      • 9.2.6. U.S.
        • 9.2.6.1. U.S Deep Learning Market Revenue, by Application, 2015 - 2024 (USD Billion)
        • 9.2.6.2. U.S Deep Learning Market Revenue, by Component, 2015 - 2024 (USD Billion)
        • 9.2.6.3. U.S Deep Learning Market Revenue, by Architecture Industry, 2015 - 2024 (USD Billion)
        • 9.2.6.4. U.S Deep Learning Market Revenue, by End-User Industry, 2015 - 2024 (USD Billion)
      • 9.2.7. Canada
        • 9.2.7.1. Canada Deep Learning Market Revenue, by Application, 2015 - 2024 (USD Billion)
        • 9.2.7.2. Canada Deep Learning Market Revenue, by Component, 2015 - 2024 (USD Billion)
        • 9.2.7.3. Canada Deep Learning Market Revenue, by Architecture Industry, 2015 - 2024 (USD Billion)
        • 9.2.7.4. Canada Deep Learning Market Revenue, by End-User Industry, 2015 - 2024 (USD Billion)
      • 9.2.8. Mexico`
        • 9.2.8.1. Mexico Deep Learning Market Revenue, by Application, 2015 - 2024 (USD Billion)
        • 9.2.8.2. Mexico Deep Learning Market Revenue, by Component, 2015 - 2024 (USD Billion)
        • 9.2.8.3. Mexico Deep Learning Market Revenue, by Architecture Industry, 2015 - 2024 (USD Billion)
        • 9.2.8.4. Mexico Deep Learning Market Revenue, by End-User Industry, 2015 - 2024 (USD Billion)
    • 9.3. Europe
      • 9.3.1. Europe Deep Learning Market Revenue, 2015 - 2024 (USD Billion)
      • 9.3.2. Europe Deep Learning Market Revenue, By Application, 2015 - 2024 (USD Billion)
      • 9.3.3. Europe Deep Learning Market Revenue, By Component, 2015 - 2024 (USD Billion)
      • 9.3.4. Europe Deep Learning Market Revenue, By Architecture Industry, 2015 - 2024 (USD Billion)
      • 9.3.5. Europe Deep Learning Market Revenue, By End-User Industry, 2015 - 2024 (USD Billion)
      • 9.3.6. U.K.
        • 9.3.6.1. U.K. Deep Learning Market Revenue, by Application, 2015 - 2024 (USD Billion)
        • 9.3.6.2. U.K. Deep Learning Market Revenue, by Component, 2015 - 2024 (USD Billion)
        • 9.3.6.3. U.K. Deep Learning Market Revenue, by Architecture Industry, 2015 - 2024 (USD Billion)
        • 9.3.6.4. U.K. Deep Learning Market Revenue, by End-User Industry, 2015 - 2024 (USD Billion)
      • 9.3.7. France
        • 9.3.7.1. France Deep Learning Market Revenue, by Application, 2015 - 2024 (USD Billion)
        • 9.3.7.2. France Deep Learning Market Revenue, by Component, 2015 - 2024 (USD Billion)
        • 9.3.7.3. France Deep Learning Market Revenue, by Architecture Industry, 2015 - 2024 (USD Billion)
        • 9.3.7.4. France Deep Learning Market Revenue, by End-User Industry, 2015 - 2024 (USD Billion)
      • 9.3.8. Germany
        • 9.3.8.1. Germany Deep Learning Market Revenue, by Application, 2015 - 2024 (USD Billion)
        • 9.3.8.2. Germany Deep Learning Market Revenue, by Component, 2015 - 2024 (USD Billion)
        • 9.3.8.3. Germany Deep Learning Market Revenue, by Architecture Industry, 2015 - 2024 (USD Billion)
        • 9.3.8.4. Germany Deep Learning Market Revenue, by End-User Industry, 2015 - 2024 (USD Billion)
      • 9.3.9. Rest of Europe
        • 9.3.9.1. Rest of Europe Deep Learning Market Revenue, by Application, 2015 - 2024 (USD Billion)
        • 9.3.9.2. Rest of Europe Deep Learning Market Revenue, by Component, 2015 - 2024 (USD Billion)
        • 9.3.9.3. Rest of Europe Deep Learning Market Revenue, by Architecture Industry, 2015 - 2024 (USD Billion)
        • 9.3.9.4. Rest of Europe Deep Learning Market Revenue, by End-User Industry, 2015 - 2024 (USD Billion)
    • 9.4. Asia Pacific
      • 9.4.1. Asia Pacific Deep Learning Market Revenue, 2015 - 2024 (USD Billion)
      • 9.4.2. Asia Pacific Deep Learning Market Revenue, By Application, 2015 - 2024 (USD Billion)
      • 9.4.3. Asia Pacific Deep Learning Market Revenue, By Component, 2015 - 2024 (USD Billion)
      • 9.4.4. Asia Pacific Deep Learning Market Revenue, By Architecture Industry, 2015 - 2024 (USD Billion)
      • 9.4.5. Asia Pacific Deep Learning Market Revenue, By End-User Industry, 2015 - 2024 (USD Billion)
      • 9.4.6. China
        • 9.4.6.1. China Deep Learning Market Revenue, by Application, 2015 - 2024 (USD Billion)
        • 9.4.6.2. China Deep Learning Market Revenue, by Component, 2015 - 2024 (USD Billion)
        • 9.4.6.3. China Deep Learning Market Revenue, by Architecture Industry, 2015 - 2024 (USD Billion)
        • 9.4.6.4. China Deep Learning Market Revenue, by End-User Industry, 2015 - 2024 (USD Billion)
      • 9.4.7. Japan
        • 9.4.7.1. Japan Deep Learning Market Revenue, by Application, 2015 - 2024 (USD Billion)
        • 9.4.7.2. Japan Deep Learning Market Revenue, by Component, 2015 - 2024 (USD Billion)
        • 9.4.7.3. Japan Deep Learning Market Revenue, by Architecture Industry, 2015 - 2024 (USD Billion)
        • 9.4.7.4. Japan Deep Learning Market Revenue, by End-User Industry, 2015 - 2024 (USD Billion)
      • 9.4.8. India
        • 9.4.8.1. India Deep Learning Market Revenue, by Application, 2015 - 2024 (USD Billion)
        • 9.4.8.2. India Deep Learning Market Revenue, by Component, 2015 - 2024 (USD Billion)
        • 9.4.8.3. India Deep Learning Market Revenue, by Architecture Industry, 2015 - 2024 (USD Billion)
        • 9.4.8.4. India Deep Learning Market Revenue, by End-User Industry, 2015 - 2024 (USD Billion)
      • 9.4.9. Rest of Asia Pacific
        • 9.4.9.1. Rest of Asia Pacific Deep Learning Market Revenue, by Application, 2015 - 2024 (USD Billion)
        • 9.4.9.2. Rest of Asia Pacific Deep Learning Market Revenue, by Component, 2015 - 2024 (USD Billion)
        • 9.4.9.3. Rest of Asia Pacific Deep Learning Market Revenue, by Architecture Industry, 2015 - 2024 (USD Billion)
        • 9.4.9.4. Rest of Asia Pacific Deep Learning Market Revenue, by End-User Industry, 2015 - 2024 (USD Billion)
    • 9.5. Latin America
      • 9.5.1. Latin America Deep Learning Market Revenue, 2015 - 2024 (USD Billion)
      • 9.5.2. Latin America Deep Learning Market Revenue, By Application, 2015 - 2024 (USD Billion)
      • 9.5.3. Latin America Deep Learning Market Revenue, By Component, 2015 - 2024 (USD Billion)
      • 9.5.4. Latin America Deep Learning Market Revenue, By Architecture Industry, 2015 - 2024 (USD Billion)
      • 9.5.5. Latin America Deep Learning Market Revenue, By End-User Industry, 2015 - 2024 (USD Billion)
      • 9.5.6. Brazil
        • 9.5.6.1. Brazil Deep Learning Market Revenue, by Application, 2015 - 2024 (USD Billion)
        • 9.5.6.2. Brazil Deep Learning Market Revenue, by Component, 2015 - 2024 (USD Billion)
        • 9.5.6.3. Brazil Deep Learning Market Revenue, by Architecture Industry, 2015 - 2024 (USD Billion)
        • 9.5.6.4. Brazil Deep Learning Market Revenue, by End-User Industry, 2015 - 2024 (USD Billion)
      • 9.5.7. Argentina
        • 9.5.7.1. Argentina Deep Learning Market Revenue, by Application, 2015 - 2024 (USD Billion)
        • 9.5.7.2. Argentina Deep Learning Market Revenue, by Component, 2015 - 2024 (USD Billion)
        • 9.5.7.3. Argentina Deep Learning Market Revenue, by Architecture Industry, 2015 - 2024 (USD Billion)
        • 9.5.7.4. Argentina Deep Learning Market Revenue, by End-User Industry, 2015 - 2024 (USD Billion)
    • 9.6. Middle East & Africa
      • 9.6.1. Middle East & Africa Deep Learning Market Revenue, 2015 - 2024 (USD Billion)
      • 9.6.2. Middle East & Africa Deep Learning Market Revenue, By Application, 2015 - 2024 (USD Billion)
      • 9.6.3. Middle East & Africa Deep Learning Market Revenue, By Component, 2015 - 2024 (USD Billion)
      • 9.6.4. Middle East & Africa Deep Learning Market Revenue, By Architecture Industry, 2015 - 2024 (USD Billion)
      • 9.6.5. The Middle East & Africa Deep Learning Market Revenue, By End-User Industry, 2015 - 2024 (USD Billion)
  •  
  • Chapter 10. Company Profiles
    • 10.1. IBM Corporation
      • 10.1.1. Overview
      • 10.1.2. Financials
      • 10.1.3. Type portfolio
      • 10.1.4. Business strategy
      • 10.1.5. Recent developments
    • 10.2. Intel Corporation
      • 10.2.1. Overview
      • 10.2.2. Financials
      • 10.2.3. Type portfolio
      • 10.2.4. Business strategy
      • 10.2.5. Recent developments
    • 10.3. NVIDIA Corporation
      • 10.3.1. Overview
      • 10.3.2. Financials
      • 10.3.3. Type portfolio
      • 10.3.4. Business strategy
      • 10.3.5. Recent developments
    • 10.4. Alphabet Inc.
      • 10.4.1. Overview
      • 10.4.2. Financials
      • 10.4.3. Type portfolio
      • 10.4.4. Business strategy
      • 10.4.5. Recent developments
    • 10.5. Advanced Micro Devices, Inc.
      • 10.5.1. Overview
      • 10.5.2. Financials
      • 10.5.3. Type portfolio
      • 10.5.4. Business strategy
      • 10.5.5. Recent developments
    • 10.6. Microsoft Corporation
      • 10.6.1. Overview
      • 10.6.2. Financials
      • 10.6.3. Type portfolio
      • 10.6.4. Business strategy
      • 10.6.5. Recent developments
    • 10.7. Arm Holdings
      • 10.7.1. Overview
      • 10.7.2. Financials
      • 10.7.3. Type portfolio
      • 10.7.4. Business strategy
      • 10.7.5. Recent developments
    • 10.8. Qualcomm Technologies, Inc.
      • 10.8.1. Overview
      • 10.8.2. Financials
      • 10.8.3. Type portfolio
      • 10.8.4. Business strategy
      • 10.8.5. Recent developments
    • 10.9. Micron Technology, Inc
      • 10.9.1. Overview
      • 10.9.2. Financials
      • 10.9.3. Type portfolio
      • 10.9.4. Business strategy
      • 10.9.5. Recent developments
    • 10.10. Amazon Web Services
      • 10.10.1. Overview
      • 10.10.2. Financials
      • 10.10.3. Type portfolio
      • 10.10.4. Business strategy
      • 10.10.5. Recent developments

Methodology

Free Analysis

Deep Learning is a part of a machine learning method and is a subset of Artificial Intelligence (AI) technology. Deep learning uses a set of algorithms for decision-making while performing certain tasks. The technology is based on the design and operation of the brain and it matches the approach used by humans to gain knowledge of certain types. This form of technology is called the artificial neural networks. 

Technological advancement in the automotive sector is preliminarily driving the market. Deep learning is used in various applications such as driver assistance systems, identifying signboards, and tracking pedestrians systems that are deployed in autonomous vehicles. Further, major automotive equipment manufacturers had spent around USD 46 billion in 2015 to develop products that support driverless vehicles. The investments are expected to increase as automotive manufacturers such as BMW, Mercedes, and Volkswagen are planning to introduce autonomous vehicles over the next five years. These developments are expected to fuel the growth of the deep learning market during the forecast period.

Global Deep Learning Market

Deep learning helps financial institutes and online retailers to detect and prevent frauds. Over the past decade, online transactions have increased owing to online shopping and introduction of mobile payment option. In 2017, nearly 40 billion global e-commerce transactions were carried out as compared to 21 billion in 2011. This generated the need for technology to protect data and prevent online fraud. Financial institutions such as Citi Bank, PayPal, J.P. Morgan, and HSBC along with others have opted for deep learning for secured transactions. Thus, global deep learning market is expected to propel due to increasing digitalization in various developing countries. On a contrary, high initial investment is expected to have an adverse effect on deep learning market growth. Nonetheless, advancements in technology along with developments in the transportation sector may open new avenues for the market in the near future.

Based on application, the global deep learning market is segmented into speech recognition, image recognition, data mining, drug discovery, driver assistance, and others. The image recognition segment is expected to hold a significant market share during the timeframe. Automotive, healthcare, media & entertainment, BFSI, and others are prominent end-user industries for deep learning market. BFSI segment is projected to grow at a substantial rate during the forecast period.

North America holds the majority of the shares in the global deep learning market and will maintain its dominance in the coming future. Increasing usage of artificial intelligence for military and defense applications along with the rapid advancements in technology are the major drivers for the market in this region. Further, the presence of significant market players in the region is predicted to propel the global deep learning market massively. Growing research & development activities is the major driving factor for the growth of deep learning markets in Asia Pacific region. The Asia Pacific is expected to grow at a significant rate during the analysis period.

Some of the key players in the deep learning market are IBM Corporation, Intel Corporation, NVIDIA Corporation, Alphabet Inc., Advanced Micro Devices Inc., Microsoft Corporation, Arm Holdings, Qualcomm Technologies Inc., Micron Technology Inc., and Amazon Web Services, among others.

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