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Deep Learning Market - Global Forecast to 2023DUBLIN, April 20, 2018 /PRNewswire/ -- The "Deep Learning Market by Offering (Hardware, Software, and Services), Application (Image Recognition, Signal Recognition, Data Mining), End-User Industry (Security, Marketing, Healthcare, Fintech, Automotive) & Geography - Global Forecast to 2023" report has been added to ResearchAndMarkets.com's offering. The overall deep learning market is estimated to be valued at USD 3.18 Billion in 2018 and is expected to reach USD 18.16 Billion by 2023, at a CAGR of 41.7% between 2018 and 2023. Major drivers for this market are improving computing power and declining hardware cost; the increasing adoption of cloud-based technology; deep learning usage in big data analytics; and growing AI adoption in customer-centric services. The deep learning market has been segmented on the basis of offerings, applications, end-user industries, and geographies. In terms of offerings, software holds the largest share of the deep learning market. Also, the market for services is expected to grow at the highest CAGR from 2018 to 2023. The increasing adoption of deep learning software solutions in various applications, such as smartphone assistants, ATMs that read checks, voice and image recognition software on social network, and software that serves up ads on many websites, is driving the growth of machine learning technology in the deep learning market. Most companies that manufacture and develop deep learning systems and related software provide both online and offline support, depending on the application. Several companies provide installation, training, and support pertaining to these systems, along with online assistance and post-maintenance of software and required services. Key Topics Covered: 1 Introduction 5.2.3.1 Presence of Limited Structured Data to Increase Demand for Deep Learning Solutions 5.2.3.2 Cumulative Spending in Healthcare, Travel, Tourism, and Hospitality Industries 5.2.4 Challenges 5.2.4.1 Lack of Flexibility and Multitasking 5.2.4.2 Deployment of Dl for Applications Such as NLP in Regional Dialects 5.3 Value Chain Analysis 5.4 Some of the Prominent Ml Libraries (Software Frameworks) 6 Deep Learning Market, By Offering 6.1 Introduction 6.2 Hardware 6.2.1 Processor 6.2.2 Memory 6.2.3 Network 6.3 Software 6.3.1 Solution (Software Framework/SDK) 6.3.2 Platform/API 6.4 Services 6.4.1 Installation 6.4.2 Training 6.4.3 Support & Maintenance 7 Deep Learning Market, By Application 7.1 Introduction 7.2 Image Recognition 7.3 Signal Recognition 7.4 Data Mining 7.5 Others (Recommender System and Drug Discovery) 8 Deep Learning Market, By End-User Industry 8.1 Introduction 8.2 Healthcare 8.2.1 Patient Data & Risk Analysis 8.2.2 Lifestyle Management & Monitoring 8.2.3 Precision Medicine 8.2.4 Inpatient Care & Hospital Management 8.2.5 Medical Imaging & Diagnostics 8.2.6 Drug Discovery 8.2.7 Virtual Assistant 8.2.8 Wearables 8.2.9 Research 8.3 Manufacturing 8.3.1 Material Movement 8.3.2 Predictive Maintenance and Machinery Inspection 8.3.3 Production Planning 8.3.4 Field Services 8.3.5 Reclamation 8.3.6 Quality Control 8.4 Automotive 8.4.1 Autonomous Driving 8.4.2 Human-Machine Interface 8.4.3 Semiautonomous Driving 8.5 Agriculture 8.5.1 Precision Farming 8.5.2 Livestock Monitoring 8.5.3 Drone Analytics 8.5.4 Agricultural Robots 8.5.5 Others 8.6 Retail 8.6.1 Product Recommendation and Planning 8.6.2 Customer Relationship Management 8.6.3 Visual Search 8.6.4 Virtual Assistant 8.6.5 Price Optimization 8.6.6 Payment Services Management 8.6.7 Supply Chain Management and Demand Planning 8.6.8 Others 8.7 Security 8.7.1 Identity and Access Management (IAM) 8.7.2 Risk and Compliance Management 8.7.3 Encryption 8.7.4 Data Loss Prevention 8.7.5 Unified Threat Management 8.7.6 Antivirus/Antimalware 8.7.7 Intrusion Detection/Prevention Systems 8.7.8 Others 8.8 Human Resources 8.8.1 Virtual Assistant 8.8.2 Sentiment Analysis 8.8.3 Scheduling Group Meetings and Interviews 8.8.4 Personalized Learning and Development 8.8.5 Applicant Tracking & Assessment 8.8.6 Employee Engagement 8.8.7 Resume Analysis 8.9 Marketing 8.9.1 Social Media Advertising 8.9.2 Search Advertising 8.9.3 Dynamic Pricing 8.9.4 Virtual Assistant 8.9.5 Content Curation 8.9.6 Sales & Marketing Automation 8.9.7 Analytics Platform 8.9.8 Others 8.10 Law 8.10.1 Ediscovery 8.10.2 Legal Research 8.10.3 Contract Analysis 8.10.4 Case Prediction 8.10.5 Compliance 8.10.6 Others 8.11 Fintech 8.11.1 Virtual Assistant 8.11.2 Business Analytics and Reporting 8.11.3 Customer Behavior Analytics 8.11.4 Others 9 Geographic Analysis 9.1 Introduction 9.2 North America 9.2.1 US 9.2.2 Canada 9.2.3 Mexico 9.3 Europe 9.3.1 UK 9.3.2 Germany 9.3.3 France 9.3.4 Italy 9.3.5 Spain 9.3.6 Rest of Europe 9.4 APAC 9.4.1 China 9.4.2 Japan 9.4.3 South Korea 9.4.4 India 9.4.5 Rest of APAC 9.5 RoW 9.5.1 Middle East and Africa 9.5.2 South America 10 Competitive Landscape 10.1 Overview 10.2 Ranking Analysis: Deep Learning Market 10.3 Competitive Situation and Trend 10.3.1 New Product Developments and Launches 10.3.2 Collaborations and Partnerships 10.3.3 Acquisitions 10.3.4 Others 11 Company Profiles 11.1 Key Players 11.1.1 Amazon Web Services (AWS) 11.1.2 Google 11.1.3 IBM 11.1.4 Intel 11.1.5 Micron Technology 11.1.6 Microsoft 11.1.7 Nvidia 11.1.8 Qualcomm 11.1.9 Samsung Electronics 11.1.10 Sensory Inc. 11.1.11 Skymind 11.1.12 Xilinx 11.2 Other Companies 11.2.1 AMD 11.2.2 General Vision 11.2.3 Graphcore 11.2.4 Mellanox Technologies 11.2.5 Huawei Technologies 11.2.6 Fujitsu 11.2.7 Baidu 11.2.8 Mythic 11.2.9 Adapteva, Inc. 11.2.10 Koniku 11.2.11 Tenstorrent For more information about this report visit https://www.researchandmarkets.com/research/htm7xp/deep_learning?w=5 Media Contact: Laura Wood, Senior Manager View original content:http://www.prnewswire.com/news-releases/deep-learning-market---global-forecast-to-2023-300633734.html SOURCE Research and Markets |