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***** マーケットレポート.jp「機械学習の世界市場予測（～2022年）」調査資料を販売開始 *****

H&Iグローバルリサーチ株式会社（本社：東京都中央区）は、この度、MarketsandMarketsが発行した「機械学習の世界市場予測（～2022年）」調査レポートの取扱・販売をMarketReport.jpサイト（取扱レポート数：15万件以上、日本最大級）にて開始しました。国内企業の海外進出、新規ビジネス機会発掘、競合他社分析などに役立つ情報レポートです。

***** レポート概要 *****
◆日本語タイトル：機械学習の世界市場予測（～2022年）
◆英語タイトル：Machine Learning Market by Vertical (BFSI, Healthcare and Life Sciences, Retail, Telecommunication, Government and Defense, Manufacturing, Energy and Utilities), Deployment Mode, Service, Organization Size, and Region – Global Forecast to 2022
◆商品コード：MAM-TC5578
◆発行会社（調査会社）：MarketsandMarkets
◆ページ数：162
◆レポート言語：英語
◆レポート形式：PDF
◆納品方法：Eメール
◆調査対象地域：グローバル
◆産業分野：IT

***** レポート目次(一部抜粋) *****
TABLE OF CONTENTS

1 INTRODUCTION 16
1.1 OBJECTIVES OF THE STUDY 16
1.2 MARKET DEFINITION 16
1.3 MARKET SCOPE 17
1.4 YEARS CONSIDERED FOR THE STUDY 18
1.5 CURRENCY 18
1.6 STAKEHOLDERS 19

2 RESEARCH METHODOLOGY 20
2.1 RESEARCH DATA 20
2.1.1 SECONDARY DATA 21
2.1.2 PRIMARY DATA 21
2.1.2.1 Breakdown of primaries 21
2.1.2.2 Key industry insights 22
2.2 MARKET SIZE ESTIMATION 23
2.2.1 BOTTOM-UP APPROACH 24
2.2.2 TOP-DOWN APPROACH 25
2.3 MICROQUADRANT RESEARCH METHODOLOGY 25
2.3.1 VENDOR INCLUSION CRITERIA 26
2.4 RESEARCH ASSUMPTIONS 26
2.5 LIMITATIONS 27

3 EXECUTIVE SUMMARY 28

4 PREMIUM INSIGHTS 36
4.1 ATTRACTIVE MARKET OPPORTUNITIES IN THE MACHINE LEARNING MARKET 36
4.2 MACHINE LEARNING MARKET: TOP 3 VERTICALS 36
4.3 LIFECYCLE ANALYSIS, BY REGION, 2017–2022 37

5 MARKET OVERVIEW AND INDUSTRY TRENDS 39
5.1 INTRODUCTION 39
5.2 MARKET DYNAMICS 39
5.2.1 DRIVERS 40
5.2.1.1 Technological advancements 40
5.2.1.2 Proliferation in data generation 40
5.2.2 RESTRAINTS 40
5.2.2.1 Lack of skilled employees 40
5.2.3 OPPORTUNITIES 41
5.2.3.1 Increasing demand for intelligent business processes 41
5.2.3.2 Increasing adoption in modern applications 41
5.2.4 CHALLENGES 41
5.2.4.1 Sensitive data security 41
5.2.4.2 Ethical implications of the algorithms deployed 42
5.3 INDUSTRY TRENDS 42
5.3.1 MACHINE LEARNING: USE CASES 42
5.3.1.1 Introduction 42
5.3.1.2 USE CASE #1: Deliver analytics solution 42
5.3.1.3 USE CASE #2: Improve cross-selling capabilities 43
5.3.1.4 USE CASE #3: Increase revenue and decrease customer incompetence 43
5.3.1.5 USE CASE #4: Market basket analysis 44
5.4 MACHINE LEARNING PROCESS 44
5.5 REGULATORY IMPLICATIONS 45
5.5.1 INTRODUCTION 45
5.5.2 SARBANES-OXLEY ACT OF 2002 45
5.5.3 GENERAL DATA PROTECTION REGULATION 46
5.5.4 BASEL 46

6 MACHINE LEARNING MARKET ANALYSIS, BY VERTICAL 47
6.1 INTRODUCTION 48
6.1.1 MACHINE LEARNING APPLICATION IN BANKING, FINANCIAL SERVICES, AND INSURANCE 49
6.1.1.1 Fraud and risk management 50
6.1.1.2 Customer segmentation 50
6.1.1.3 Sales and marketing campaign management 50
6.1.1.4 Investment prediction 51
6.1.1.5 Digital assistance 51
6.1.1.6 Others 51
6.1.2 MACHINE LEARNING APPLICATION IN HEALTHCARE AND LIFE SCIENCES 51
6.1.2.1 Disease identification and diagnosis 52
6.1.2.2 Image analytics 53
6.1.2.3 Personalized treatment 53
6.1.2.4 Drug discovery/manufacturing 53
6.1.2.5 Others 53
6.1.3 MACHINE LEARNING APPLICATION IN RETAIL 53
6.1.3.1 Inventory planning 55
6.1.3.2 Recommendation engines 55
6.1.3.3 Upsells and cross channel marketing 55
6.1.3.4 Segmentation and targeting 55
6.1.3.5 Others 55
 
6.1.4 MACHINE LEARNING APPLICATION IN TELECOMMUNICATION 56
6.1.4.1 Customer analytics 57
6.1.4.2 Network security 57
6.1.4.3 Network optimization 58
6.1.4.4 Others 58
6.1.5 MACHINE LEARNING APPLICATION IN GOVERNMENT AND DEFENSE 58
6.1.5.1 Autonomous defense system 60
6.1.5.2 Threat intelligence 60
6.1.5.3 Others 60
6.1.6 MACHINE LEARNING APPLICATION IN MANUFACTURING 61
6.1.6.1 Predictive maintenance 62
6.1.6.2 Revenue estimation 62
6.1.6.3 Demand forecasting 62
6.1.6.4 Supply chain management 63
6.1.6.5 Others 63
6.1.7 MACHINE LEARNING APPLICATION IN ENERGY AND UTILITIES 63
6.1.7.1 Power/energy usage analytics 65
6.1.7.2 Seismic data processing 65
6.1.7.3 Carbon emission 65
6.1.7.4 Smart grid management 65
6.1.7.5 Others 65
6.1.8 OTHER APPLICATIONS 66

7 MACHINE LEARNING MARKET ANALYSIS, BY DEPLOYMENT MODE 67
7.1 INTRODUCTION 68
7.2 CLOUD 69
7.3 ON-PREMISES 69

8 MACHINE LEARNING MARKET ANALYSIS, BY ORGANIZATION SIZE 70
8.1 INTRODUCTION 71
8.2 LARGE ENTERPRISES 72
8.3 SMALL AND MEDIUM-SIZED ENTERPRISES 72

9 MACHINE LEARNING MARKET ANALYSIS, BY SERVICE 73
9.1 INTRODUCTION 74
9.2 PROFESSIONAL SERVICES 75
9.3 MANAGED SERVICES 75
 

10 GEOGRAPHIC ANALYSIS 76
10.1 INTRODUCTION 77
10.2 NORTH AMERICA 79
10.2.1 BY VERTICAL 81
10.2.1.1 Machine learning application trends in BFSI 82
10.2.1.2 Machine learning application trends in healthcare and life sciences 83
10.2.1.3 Machine learning application trends in retail 84
10.2.1.4 Machine learning application trends in telecommunication 84
10.2.1.5 Machine learning application trends in government and defense 85
10.2.1.6 Machine learning application trends in manufacturing 85
10.2.1.7 Machine learning application trends in energy and utilities 86
10.2.2 BY ORGANIZATION SIZE 86
10.2.3 BY DEPLOYMENT MODE 86
10.2.4 BY SERVICE 87
10.3 EUROPE 87
10.3.1 BY VERTICAL 88
10.3.1.1 Machine learning application trends in BFSI 89
10.3.1.2 Machine learning application trends in healthcare and life sciences 89
10.3.1.3 Machine learning application trends in retail 90
10.3.1.4 Machine learning application trends in telecommunication 90
10.3.1.5 Machine learning application trends in government and defense 91
10.3.1.6 Machine learning application trends in manufacturing 91
10.3.1.7 Machine learning application trends in energy and utilities 92
10.3.2 BY ORGANIZATION SIZE 92
10.3.3 BY DEPLOYMENT MODE 93
10.3.4 BY SERVICE 93
10.4 ASIA PACIFIC 94
10.4.1 BY VERTICAL 95
10.4.1.1 Machine learning application trends in BFSI 96
10.4.1.2 Machine learning application trends in healthcare and life sciences 96
10.4.1.3 Machine learning application trends in retail 97
10.4.1.4 Machine learning application trends in telecommunication 97
10.4.1.5 Machine learning application trends in government and defense 98
10.4.1.6 Machine learning application trends in manufacturing 98
10.4.1.7 Machine learning application trends in energy and utilities 99
10.4.2 BY ORGANIZATION SIZE 99
10.4.3 BY DEPLOYMENT MODE 100
10.4.4 BY SERVICE 100
 
10.5 MIDDLE EAST AND AFRICA 101
10.5.1 BY VERTICAL 101
10.5.1.1 Machine learning application trends in BFSI 102
10.5.1.2 Machine learning application trends in healthcare and life sciences 103
10.5.1.3 Machine learning application trends in retail 103
10.5.1.4 Machine learning application trends in telecommunication 104
10.5.1.5 Machine learning application trends in government and defense 104
10.5.1.6 Machine learning application trends in manufacturing 105
10.5.1.7 Machine learning application trends in energy and utilities 105
10.5.2 BY ORGANIZATION SIZE 106
10.5.3 BY DEPLOYMENT MODE 106
10.5.4 BY SERVICE 106
10.6 LATIN AMERICA 107
10.6.1 BY VERTICAL 107
10.6.1.1 Machine learning application trends in BFSI 108
10.6.1.2 Machine learning application trends in healthcare and life sciences 109
10.6.1.3 Machine learning application trends in retail 109
10.6.1.4 Machine learning application trends in telecommunication 110
10.6.1.5 Machine learning application trends in government and defense 110
10.6.1.6 Machine learning application trends in manufacturing 110
10.6.1.7 Machine learning application trends in energy and utilities 111
10.6.2 BY ORGANIZATION SIZE 111
10.6.3 BY DEPLOYMENT MODE 112
10.6.4 BY SERVICE 112

11 COMPETITIVE LANDSCAPE 113
11.1 MARKET RANKING FOR THE MACHINE LEARNING MARKET, 2017 113
 

12 COMPANY PROFILES 114
(Business Overview, Strength of product portfolio, Business strategy excellence, Recent developments)*

12.1 INTERNATIONAL BUSINESS MACHINES CORPORATION 114
12.2 MICROSOFT CORPORATION 117
12.3 SAP SE 120
12.4 SAS INSTITUTE INC. 124
12.5 AMAZON WEB SERVICES, INC. 127
12.6 BIGML, INC. 130
12.7 GOOGLE INC. 133
12.8 FAIR ISAAC CORPORATION 136
12.9 BAIDU, INC. 139
12.10 HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP 142
12.11 INTEL CORPORATION 145
12.12 H2O.AI 148
*Details on Overview, Strength of product portfolio, Business strategy excellence, Recent developments might not be captured in case of unlisted companies.

13 APPENDIX 151
13.1 DISCUSSION GUIDE 151
13.2 KNOWLEDGE STORE: MARKETSANDMARKETS’ SUBSCRIPTION PORTAL 156
13.3 INTRODUCING RT: REAL-TIME MARKET INTELLIGENCE 158
13.4 AVAILABLE CUSTOMIZATIONS 159
13.5 RELATED REPORTS 159
13.6 AUTHOR DETAILS 160

・イントロダクション
・エグゼクティブサマリー
・機械学習の世界市場：市場インサイト
・機械学習の世界市場：市場概観/市場動向
・機械学習の世界市場：産業動向
・機械学習の世界市場：産業別分析/市場規模
・機械学習の世界市場：地域別分析/市場規模
・機械学習のアジア市場規模予測
・機械学習のヨーロッパ市場規模予測
・機械学習のアメリカ市場規模予測
・機械学習の世界市場動向
・機械学習の世界市場：競争状況
・機械学習の世界市場：関連企業分析
…

※「機械学習の世界市場予測（～2022年）」レポート詳細紹介ページ
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