Deep Learning Market by Component (Hardware, Software & Services), Application (Image Recognition, Signal Recognition & Data Mining), and End-User Industry (Law, Retail, Fintech, Healthcare, Automotive, Marketing, Manufacturing and Human Resources) - Global Opportunity Analysis and Industry Forecast, 2019-2026
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May 2020 |
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Global Deep Learning Market Outlook -2026
Deep learning is a subfield of machine learning that consist of a series of computer instructions or algorithms that is inspired by the function and structure of the brain. Deep learning is widely known as artificial neural networks or deep neural networks. Deep neural networks are a set of algorithms that are designed to recognize patterns and are built with components of larger machine-learning applications, which includes algorithms for reinforcement learning, classification, and regression. Examples of deep learning applications includes driverless cars, voice control in consumer devices, and many others, which help boost the deep learning market size.
Rising need to improve computing power and decline hardware cost owing to deep learning algorithms capability to run or execute faster on a GPU as compared to a CPU is resulting into high adoption of deep learning technologies among various industries. Also, proliferation of deep learning integration with big data analytics is expected to drive the growth of the global deep learning market during the forecast period. However, lack of technical expertise in deep learning and absence of standards and protocols are the factors that can hamper the deep learning market growth.
The global deep learning market is segmented based on component, application, end-user industry, and region. Based on component, it is categorized into hardware, software, and services. Based on application, it is classified into image recognition, signal recognition, data mining, and others. Based on end-user industry, it is divided into law, retail, fintech, healthcare, automotive, marketing, manufacturing, human resources, and others. Based on region, it is analyzed across North America, Europe, Asia-Pacific, and LAMEA.
The key players profiled in the global deep learning market analysis are Sensory, Inc., Skymind, Inc., Xilinx, Inc., Google LLC, IBM Corporation, Intel Corporation, Micron Technology, Inc., Microsoft Corporation, Nvidia Corporation, Amazon Web Services, Inc., Qualcomm Incorporated, and Samsung Electronics Co., Ltd
KEY BENEFITS FOR STAKEHOLDERS
- The study provides an in-depth analysis of the global deep learning market size along with the current trends and future estimations to elucidate the imminent investment pockets.
- Information about key drivers, restraints, and opportunities and their impact analysis on the market size is provided.
- Porter’s five forces analysis illustrates the potency of buyers and suppliers operating in the industry.
- The quantitative analysis of the global deep learning market industry from 2019 to 2026 is provided to determine the market potential.
KEY MARKET SEGMENTS
BY COMPONENT
- Hardware
- Software
- Services
BY APPLICATION
- Image Recognition
- Signal Recognition
- Data Mining
- Others
BY END-USER INDUSTRY
- Law
- Retail
- Fintech
- Healthcare
- Automotive
- Marketing
- Manufacturing
- Human Resources
- Others
BY REGION
- North America
- U.S.
- Canada
- Europe
- UK
- Germany
- France
- Rest of Europe
- Asia-Pacific
- China
- India
- Japan
- Singapore
- Rest of Asia-Pacific
- LAMEA
- Latin America
- Middle East
- Africa
KEY MARKET PLAYERS PROFILED IN THE REPORT
- Sensory, Inc.
- Skymind, Inc.
- Xilinx, Inc.
- Google LLC
- IBM Corporation
- Intel Corporation
- Micron Technology, Inc.
- Microsoft Corporation
- Nvidia Corporation
- Amazon Web Services, Inc.
- Qualcomm Incorporated
- Samsung Electronics Co., Ltd
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We refer a broad array of industry sources for our secondary, which typically include; however, not limited to: Company SEC filings, annual reports, company websites, broker & financial reports and investor presentations for competitive scenario and shape of the industry
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- Scientific and technical writings for product information and related preemptions
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