The growing need for improved human and system interaction will drive the growth prospects for the global deep learning system market during the forecast period. Since deep learning systems can provide expert assistance, they help humans to extend their capabilities.
These systems first develop a deep domain insight and provide this information to the end-users in a timely, natural, and usable way. For instance, in the financial sector, deep learning systems help bank employees extend their work capabilities and allow financial institutions to concentrate more on customer interaction rather than the traditional transaction-based approach.
Deep learning systems also enable customized and self-service options for customers and assist employees in offering tailored recommendations for the customers' specific needs and tolerance for risks.
Deep learning is a new area in machine learning research and focuses on artificial learning, the primary objective of machine learning. Deep learning deals with learning multiple levels of representation and abstraction that helps make sense of data such as images, sound, and text.
The deep learning market has a huge potential across various industries such as advertisement, finance, and automotive. The major factors driving the deep learning market globally are the robust R&D for the development of better processing hardware and increasing adoption of cloud-based technology for deep learning.
Deep learning has self-learning capability that provides faster processing and higher accuracy. Alike image recognition, in cyber security, most of new malware and threats are very small alterations of the existing ones.
Only a few of them are new malware that are substantial mutations of current malicious threat.
Deep learning brings technology a step closer to humans by supporting them in decision-making in numerous areas of life and work. The integration of deep learning applications with self-learning IT systems within an organization helps in communicating with people and other computer systems in real time.
It also aids in recollecting previous interactions that assist in drawing conclusions independently while rapidly processing large quantities of data from highly diverse sources.
In this report, the global Deep Learning System market is valued at USD XX million in 2016 and is expected to reach USD XX million by the end of 2022, growing at a CAGR of XX% between 2016 and 2022.
Geographically, this report is segmented into several key Regions, with production, consumption, revenue (million USD), market share and growth rate of Deep Learning System in these regions, from 2012 to 2022 (forecast), covering
Table of Content:-
Global Deep Learning System Market Research Report 2017
1 Deep Learning System Market Overview
1.1 Product Overview and Scope of Deep Learning System
1.2 Deep Learning System Segment by Type (Product Category)
1.2.1 Global Deep Learning System Production and CAGR (%) Comparison by Type (Product Category) (2012-2022)
1.2.2 Global Deep Learning System Production Market Share by Type (Product Category) in 2016
1.3 Global Deep Learning System Segment by Application
1.3.1 Deep Learning System Consumption (Sales) Comparison by Application (2012-2022)
1.3.3 Aerospace, Military & Defense
1.4 Global Deep Learning System Market by Region (2012-2022)
1.4.1 Global Deep Learning System Market Size (Value) and CAGR (%) Comparison by Region (2012-2022)
1.4.2 United States Status and Prospect (2012-2022)
1.4.3 EU Status and Prospect (2012-2022)
1.4.4 China Status and Prospect (2012-2022)
1.4.5 Japan Status and Prospect (2012-2022)
1.4.6 South Korea Status and Prospect (2012-2022)
1.4.7 Taiwan Status and Prospect (2012-2022)
1.5 Global Market Size (Value) of Deep Learning System (2012-2022)
1.5.1 Global Deep Learning System Revenue Status and Outlook (2012-2022)
1.5.2 Global Deep Learning System Capacity, Production Status and Outlook (2012-2022)
2 Global Deep Learning System Market Competition by Manufacturers
2.1 Global Deep Learning System Capacity, Production and Share by Manufacturers (2012-2017)
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