Global Deep Learning System Market 2016-2020

ディープラーニング(深層学習)システムの世界市場2016-2020

◆タイトル:Global Deep Learning System Market 2016-2020
◆商品コード:IRTNTR10846
◆調査・発行会社:Technavio (Infiniti Research Ltd.)
◆発行日:2016年11月18日
◆ページ数:64
◆資料形式:PDF / 英語
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【資料の概要】

当調査レポートでは、ディープラーニング(深層学習)システムの世界市場について調査・分析し、エグゼクティブサマリー、市場概観、市場概観、業界の構造分析、ディープラーニング(深層学習)システムの世界市場規模及び予測、製品別分析、需要先別分析、地域別分析/市場規模、市場の成長要因、市場の課題、市場動向、競争状況などの情報をお届けいたします。

About Deep Learning System
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.

Technavio’s analysts forecast the global deep learning system market to grow at a CAGR of 38.73% during the period 2016-2020.

[Covered in this report]
The report covers the present scenario and the growth prospects of the global deep learning system market for 2016-2020. To calculate the market size, the report provides a list of vendors and the detailed profiles of the major vendors in the global deep learning system market.

The market is divided into the following segments based on geography:
• Americas
• APAC
• EMEA

Technavio’s report, Global Deep Learning System Market 2016-2020, has been prepared based on an in-depth market analysis with inputs from industry experts. The report covers the market landscape and its growth prospects over the coming years. The report also includes a discussion of the key vendors operating in this market.

[Key vendors]
• Alphabet
• BVLC
• Facebook
• LISA lab
• Microsoft
• Nervana Systems

[Other prominent vendors]
• Affectiva
• Clarifai
• Deep Genomics
• Deep Instinct
• Ditto Labs
• Enlitic
• Gridspace
• Indico
• MarianaIQ
• MetaMind
• Ripjar

[Market driver]
• Surging demand for more knowledge about decisions and processes.
• For a full, detailed list, view our report

[Market challenge]
• Advances in learning process.
• For a full, detailed list, view our report

[Market trend]
• Rising need for detecting new malware for cyber security.
• For a full, detailed list, view our report

[Key questions answered in this report]
• What will the market size be in 2020 and what will the growth rate be?
• What are the key market trends?
• What is driving this market?
• What are the challenges to market growth?
• Who are the key vendors in this market space?
• What are the market opportunities and threats faced by the key vendors?
• What are the strengths and weaknesses of the key vendors?

※You can request one free hour of our analyst’s time when you purchase this market report. Details are provided within the report.

【資料の目次】

PART 01: Executive summary
• Highlights
• Overview of revenue

PART 02: Scope of the report
• Market overview
• Market segmentation
• Geographical information
• Vendor selection
• Summation errors

PART 03: Market research methodology
• Research methodology
• Economic indicators

PART 04: Introduction
• Key market highlights

PART 05: Market landscape

PART 06: Market size and forecast

PART 07: Market segmentation by end-user
• BFSI
• Retail
• Healthcare
• Others

PART 08: Market segmentation by product
• Hardware
• Software and applications
• Services

PART 09: Geographical segmentation

PART 10: Market drivers
• Surging demand for more knowledge about decisions and processes
• Growing need for improved human and system interaction
• Increasing need for discovering useful insights from available information
• Increased deployment of LTE wireless broadband

PART 11: Impact of drivers

PART 12: Market challenges
• Advances in learning process
• Application of cross-layers
• Lack of experienced talent

PART 13: Impact of drivers and challenges

PART 14: Market trends
• Rising need for detecting new malware for cyber security
• Growing government investment in IoT

PART 15: Five forces model

PART 16: Vendor landscape
• Competitive scenario
• Top-vendor offerings
• Vendor matrix

PART 17: Key vendor profiles
• Vendor profiles

PART 18: Prominent vendors
• Prominent deep learning frameworks and providers
• Prominent deep learning software vendors

PART 19: Assumptions
• Market assumptions

PART 20: Appendix
• List of abbreviations

PART 21: Explore Technavio

[List of Exhibits]

Exhibit 01: Overview of revenue 2015
Exhibit 02: Major countries covered in market analysis
Exhibit 03: Relationship between different sub-fields in AI
Exhibit 04: Conventional neural network architecture
Exhibit 05: Deep learning network architecture
Exhibit 06: Broad categories of deep learning architectures
Exhibit 07: Some examples of supervised and unsupervised/semi-supervised learning algorithms
Exhibit 08: Five critical dimensions for evolution of deep learning systems
Exhibit 09: Global deep learning system market 2015-2020 ($ millions)
Exhibit 10: Global deep learning system market by product 2015
Exhibit 11: Global deep learning system market by geography 2015 and 2020 (% share)
Exhibit 12: Global deep learning system market by geography 2015 and 2020 ($ millions)
Exhibit 13: Deep learning system market in Americas 2015-2020 ($ millions)
Exhibit 14: Deep learning system market in EMEA 2015-2020 ($ millions)
Exhibit 15: Deep learning system market in APAC 2015-2020 ($ millions)
Exhibit 16: Impact of drivers
Exhibit 17: Impact of drivers and challenges
Exhibit 18: Global investments in IoT
Exhibit 19: Five forces model
Exhibit 20: Products offerings
Exhibit 21: Vendor matrix by features
Exhibit 22: Vendor matrix by supported interface
Exhibit 23: Vendor matrix by speed
Exhibit 24: Alphabet: Products and features
Exhibit 25: BVLC: Products and features
Exhibit 26: Facebook: Products and features
Exhibit 27: LISA lab: Key products and features
Exhibit 28: Microsoft: Key products and features
Exhibit 29: Nervana Systems: Key products and features
Exhibit 30: Prominent deep learning frameworks and providers
Exhibit 31: Prominent vendors in global deep learning system market
Exhibit 32: Market assumptions



【掲載企業】

Alphabet, BVLC, Facebook, LISA lab, Microsoft, Nervana Systems, Affectiva, Clarifai, Deep Genomics, Deep Instinct, Ditto Labs, Enlitic, Gridspace, Indico, MarianaIQ, MetaMind, Ripjar.

【資料のキーワード】

ディープラーニング、深層学習システム

【調査方法】

一次資料による調査(業界専門家、ベンダー、代理店、顧客等を対象にしたデプスインタビュー調査など)及び二次資料による調査(Technavio独自のプラットフォーム、産業書籍、企業報告書、ニュース記事、アナリストレポート、貿易協会、政府機関発行データなど)

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