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Deep Learning Market - Global Forecast to 2023

DUBLIN, 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.

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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

2 Research Methodology

3 Executive Summary

4 Premium Insights
4.1 Attractive Opportunities in Deep Learning Market
4.2 Deep Learning Market, By Offering
4.3 Deep Learning Market, By Hardware
4.4 Deep Learning Market in APAC, By End-User Industry and Country
4.5 Deep Learning Market, By Country

5 Market Overview
5.1 Introduction
5.2 Market Dynamics
5.2.1 Drivers
5.2.1.1 Improving Computing Power and Declining Hardware Cost
5.2.1.2 Increasing Adoption of Cloud-Based Technology
5.2.1.3 Deep Learning Usage in Big Data Analytics
5.2.1.4 Growing AI Adoption in Customer-Centric Services
5.2.2 Restraints
5.2.2.1 Increasing Complexity in Hardware Due to Complex Algorithm Used in Deep Learning Technology
5.2.2.2 Lack of Technical Expertise and Absence of Standards and Protocols
5.2.3 Opportunities
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

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