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MLaaS(Machine Learning as a Service的)全球市场 - 产业规模，占有率，趋势，机会，预测:各零件，各组织规模，各用途，各终端用户，各地区，各竞争(2018年～2028年)
市场调查报告书
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1166604

MLaaS(Machine Learning as a Service的)全球市场 - 产业规模，占有率，趋势，机会，预测:各零件，各组织规模，各用途，各终端用户，各地区，各竞争(2018年～2028年)

Machine Learning as a Service Market- Global Industry Size, Share, Trends, Opportunities, and Forecast 2018-2028F Segmented By Component, By Organization Size, By Application, By End User, By Region, Competition
出版日期: | 出版商: TechSci Research | 英文 74 Pages | 商品交期: 2-3个工作天内

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简介目录

全球MLaaS(Machine Learning as a Service的)市场规模，预计至2028年以2位数的年复合成长率成长。

市场成长的要素，是云端基础的解决方案的日益采用，巨量资料的用途持续增加。再加上技术纯熟劳工少，及资料保全的缺乏，在整个预测期内估计有阻碍全球MLaaS(Machine Learning as a Service)市场成长的可能性。

本报告提供全球MLaaS(Machine Learning as a Service)市场相关调查，市场概要，VOC分析，各市场区隔、各地区的预测，促进因素和课题，COVID-19影响，市场趋势，企业简介等资讯。

目录

第1章 服务概要

第2章 调查手法

第3章 摘要整理

第4章 全球MLaaS(Machine Learning as a Service)市场上COVID-19的影响

第5章 VOC

  • MLaaS(Machine Learning as a Service的)认知度
  • MLaaS(Machine Learning as a Service的)主要用途
  • MLaaS(Machine Learning as a Service)的主要的优点
  • 主要供应商选择的参数
  • MLaaS(Machine Learning as a Service)采用时主要的选择范围
  • 主要供应商的课题

第6章 全球MLaaS(Machine Learning as a Service)市场预测

  • 市场规模与预测
    • 各金额
  • 市场占有率与预测
    • 各零件(解决方案，服务)
    • 各组织规模(大企业，中小企业)
    • 各用途(银行、金融服务、保险，医疗保健、医药品，电子商务、零售，媒体、娱乐，IT、通讯，其他)
    • 各终端用户(IT、通讯，汽车，医疗保健，航太、防卫，零售，政府，银行、金融服务、保险)
    • 各地区
    • 重要点
    • 各企业
  • 市场地图(各零件，各组织规模，各用途，各终端用户，各地区)

第7章 北美的MLaaS(Machine Learning as a Service)市场预测

  • 市场规模与预测
    • 各金额
  • 市场占有率与预测
    • 各零件
    • 各组织规模
    • 各用途
    • 各终端用户
    • 各国
    • 重要点
  • 北美:各国分析
    • 美国
    • 加拿大
    • 墨西哥

第8章 欧洲的MLaaS(Machine Learning as a Service)市场预测

  • 市场规模与预测
    • 各金额
  • 市场占有率与预测
    • 各零件
    • 各组织规模
    • 各用途
    • 各终端用户
    • 各国
    • 重要点
  • 欧洲:各国分析
    • 德国
    • 英国
    • 法国
    • 义大利
    • 西班牙

第9章 亚太地区的MLaaS(Machine Learning as a Service)市场预测

  • 市场规模与预测
    • 各金额
  • 市场占有率与预测
    • 各零件
    • 各组织规模
    • 各用途
    • 各终端用户
    • 各国
    • 重要点
  • 亚太地区:各国分析
    • 中国
    • 日本
    • 印度
    • 韩国
    • 澳洲

第10章 中东、非洲的MLaaS(Machine Learning as a Service)市场预测

  • 市场规模与预测
    • 各金额
  • 市场占有率与预测
    • 各零件
    • 各组织规模
    • 各用途
    • 各终端用户
    • 各国
    • 重要点
  • 中东、非洲:各国分析
    • 沙乌地阿拉伯
    • 阿拉伯联合大公国
    • 南非

第11章 南美的MLaaS(Machine Learning as a Service)市场预测

  • 市场规模与预测
    • 各金额
  • 市场占有率与预测
    • 各零件
    • 各组织规模
    • 各用途
    • 各终端用户
    • 各国
    • 重要点
  • 南美:各国分析
    • 巴西
    • 阿根廷
    • 哥伦比亚

第12章 市场动态

  • 促进因素
  • 课题

第13章 市场趋势与发展

  • 客户支援活动增加
  • 智慧后勤部门和营运
  • 在零售领域的机器学习的使用增加
  • 合併和收购
  • 巨量资料的急剧成长

第14章 企业简介

  • Google Inc
  • SAS Institute Inc
  • Fair Isaac Corporation
  • Hewlett Packard Enterprise Development LP
  • Yottamine Analytics Inc.
  • Amazon Web Services
  • BigML, Inc.
  • Microsoft Corporation
  • IBM Corporation
  • Broadcom Corporation

第15章 策略性建议

第16章 免责声明

简介目录
Product Code: 14234

Global machine learning as a service market is anticipated to grow at double digit CAGR through 2028 on account of rising adoption of cloud-based solutions and increasing application of big data. Additionally, it is estimated that the limited availability of skilled labour and a lack of data security can hamper the growth of the machine learning as a service (MLaaS) market globally throughout the forecasted period. The term "Machine Learning as a Service" (MLaaS) refers to a group of services which includes several cloud-based platforms using machine learning techniques to offer dedicated solutions. Furthermore, MLaaS reduces infrastructure-related issues such as data pre-processing, model training, model evaluation, and, ultimately, predictions.

Rising adoption of cloud-based services

, Several industry verticals utilize major cloud-based solutions to manage business operations. With cloud-based technologies being majorly used in various organizations and enterprises; data interchange is facilitated by the simplicity with which these connections are established. This makes it possible to access the information within the organization, increasing the latter's cost-effectiveness. For instance, Infosys Ltd launched industry cloud platform for organizations in 2022 to increase innovation and business value in the cloud across the financial services industry.

Lack of skilled resources

Developers can now design efficient cloud-based business operation solutions with the expanding adoption of cloud technologies and desirable delivery techniques across numerous industry verticals. To speed up the ML integration process, SMEs in the MLaaS industry prefer cloud-based services. Eliminating tedious work improves an organization's efficiency without adding more people. Though, lack of trained consultants, compliance problems, and regulatory limitations are some obstacles preventing this market's expansion. Therefore, in order to improve uniformity in the market environment, market participants should collaborate with governmental and regulatory agencies to improve the uniformity in the market environment.

Growing IoT in business operations

The information technology industry is expanding due to the increasing popularity of social media platforms and cloud computing technologies. Today, cloud computing services are extensively used by various companies that offer enterprise storage solutions. The ability to analyze real time data online using cloud storage is a benefit. Thanks to cloud computing, data analysis is now possible at any time and location. Businesses may also digitally access critical data from linked data warehouses and save money on infrastructure and storage costs by utilizing cloud and ML, which includes trends in customer behaviour and purchasing. The growth of cloud computing has led to the development of MLaaS industry. AI systems employ ML to speed up learning, self-correction, and reasoning. AI applications include expert systems, speech recognition, and machine vision, to name a few. Hence, AI is becoming increasingly popular as a result of modern initiatives like big data infrastructure and cloud computing.

Market Segments

Global Machine Learning as a Service Market is segmented into by component, by organization size, by application, by end-user and by region. Based on component, the market is segmented into Solution and Service. Based on Organization Size, the market is segmented into Small and Medium-Sized Enterprises and Large Enterprises. Based on Application, the market is segmented into Marketing & Advertising, Fraud Detection & Risk Management, Computer vision, Security & Surveillance, Predictive analytics, Natural Language Processing, Augmented & Virtual Reality, Others. Based on End User, the market is further segmented into IT and Telecom, Automotive, Healthcare, Aerospace and Defense, Retail, Government, BFSI.

Market Players

Major market players in the Global Machine Learning as a Service Market are Google Inc, SAS Institute Inc, Fair Isaac Corporation, Hewlett Packard Enterprise Development LP, Yottamine Analytics Inc., Amazon Web Services, BigML, Inc., Microsoft Corporation, IBM Corporation, Broadcom Corporation

Recent Developments

  • Inflection AI received one of the largest fundraising rounds for artificial machine learning in June 2022, amounting to USD 225 million. It is said to be a startup for AI and machine learning. Venture capitalists have provided it with equity financing worth USD 225 million.
  • Vertex AI, a new managed machine learning platform that enables users to maintain and deploy AI models based on client needs, was announced by Google Cloud in May 2021.

Report Scope:

In this report, Global Machine Learning as a Service Market has been segmented into following categories, in addition to the industry trends which have also been detailed below:

  • Machine Learning as a Service Market, By Component:

Solution

Service

  • Machine Learning as a Service Market, By Organization Size:

Small and Medium-Sized Enterprises

Large Enterprises

  • Machine Learning as a Service Market, By Application:

Marketing & Advertising

Fraud Detection & Risk Management

Computer vision

Security & Surveillance

Predictive analytics

Natural Language Processing

Augmented & Virtual Reality

Others

  • Machine Learning as a Service Market, By End User:

IT and Telecom

Automotive

Healthcare

Aerospace and Defense

Retail

Government

BFSI

  • Machine Learning as a Service Market, By Region:

North America

  • United States
  • Canada
  • Mexico

Asia-Pacific

  • China
  • Japan
  • India
  • South Korea
  • Australia
  • Rest of Asia-Pacific

Europe

  • Germany
  • UK
  • France
  • Italy
  • Spain
  • Rest of Europe

MEA

  • Saudi Arabia
  • UAE
  • South Africa
  • Rest of MEA

South America

  • Brazil
  • Argentina
  • Colombia
  • Rest of South America

Competitive Landscape

Company Profiles: Detailed analysis of the major companies present in Global Machine Learning as a Service Market.

Available Customizations:

Global Machine Learning as a Service Market with the given market data, Tech Sci Research offers customizations according to a company's specific needs. The following customization options are available for the report:

Company Information

  • Detailed analysis and profiling of additional market players (up to five).

Table of Contents

1. Service Overview

  • 1.1. Market Definition
  • 1.2. Scope of the Study

2. Research Methodology

  • 2.1. Baseline Methodology
  • 2.2. Methodology Followed for Calculation of Market Size
  • 2.3. Methodology Followed for Calculation of Market Shares
  • 2.4. Methodology Followed for Forecasting

3. Executive Summary

4. Impact of COVID-19 on Global Machine Learning as a Service Market

5. Voice of Customer

  • 5.1. Awareness of Machine Learning as a Service
  • 5.2. Major Applications of Machine Learning as a Service
  • 5.3. Key benefits of Machine Learning as a Service
  • 5.4. Key vendor selection parameter
  • 5.5. Major selection in adopting Machine Learning as a Service
  • 5.6. Key vendor challenges

6. Global Machine Learning as a Service Market Outlook

  • 6.1. Market Size & Forecast
    • 6.1.1. By Value
  • 6.2. Market Share & Forecast
    • 6.2.1. By Component (Solution, Service)
    • 6.2.2. By Organization Size (Large Enterprises, Small and Medium-Sized Enterprises)
    • 6.2.3. By Application (BFSI, Healthcare & Pharmaceuticals, E-commerce & Retail, Media & Entertainment, IT & Telecom, and Others)
    • 6.2.4. By End-User (IT and Telecom, Automotive, Healthcare, Aerospace and Defense, Retail, Government, BFSI)
    • 6.2.5. By Region
    • 6.2.6. Key Takeaways
    • 6.2.7. By Company (2022)
  • 6.3. Market Map (By Component, By Organization Size, By Application, By End-User, By Region)

7. North America Machine Learning as a Service Market Outlook

  • 7.1. Market Size & Forecast
    • 7.1.1. By Value
  • 7.2. Market Share & Forecast
    • 7.2.1. By Component
    • 7.2.2. By Organization Size
    • 7.2.3. By Application
    • 7.2.4. By End-User
    • 7.2.5. By Country
    • 7.2.6. Key Takeaways
  • 7.3. North America: Country Analysis
    • 7.3.1. United States Machine Learning as a Service Market Outlook
      • 7.3.1.1. Market Size & Forecast
        • 7.3.1.1.1. By Value
      • 7.3.1.2. Market Share & Forecast
        • 7.3.1.2.1. By Component
        • 7.3.1.2.2. By Organization Size
        • 7.3.1.2.3. By Application
        • 7.3.1.2.4. By End-User
    • 7.3.2. Canada Machine Learning as a Service Market Outlook
      • 7.3.2.1. Market Size & Forecast
        • 7.3.2.1.1. By Value
      • 7.3.2.2. Market Share & Forecast
        • 7.3.2.2.1. By Component
        • 7.3.2.2.2. By Organization Size
        • 7.3.2.2.3. By Application
        • 7.3.2.2.4. By End-User
    • 7.3.3. Mexico Machine Learning as a Service Market Outlook
      • 7.3.3.1. Market Size & Forecast
        • 7.3.3.1.1. By Value
      • 7.3.3.2. Market Share & Forecast
        • 7.3.3.2.1. By Component
        • 7.3.3.2.2. By Organization Size
        • 7.3.3.2.3. By Application
        • 7.3.3.2.4. By End-User

8. Europe Machine Learning as a Service Market Outlook

  • 8.1. Market Size & Forecast
    • 8.1.1. By Value
  • 8.2. Market Share & Forecast
    • 8.2.1. By Component
    • 8.2.2. By Organization Size
    • 8.2.3. By Application
    • 8.2.4. By End-User
    • 8.2.5. By Country
    • 8.2.6. Key Takeaways
  • 8.3. Europe: Country Analysis
    • 8.3.1. Germany Machine Learning as a Service Market Outlook
      • 8.3.1.1. Market Size & Forecast
        • 8.3.1.1.1. By Value
      • 8.3.1.2. Market Share & Forecast
        • 8.3.1.2.1. By Component
        • 8.3.1.2.2. By Organization Size
        • 8.3.1.2.3. By Application
        • 8.3.1.2.4. By End-User
    • 8.3.2. United Kingdom Machine Learning as a Service Market Outlook
      • 8.3.2.1. Market Size & Forecast
        • 8.3.2.1.1. By Value
      • 8.3.2.2. Market Share & Forecast
        • 8.3.2.2.1. By Component
        • 8.3.2.2.2. By Organization Size
        • 8.3.2.2.3. By Application
        • 8.3.2.2.4. By End-User
    • 8.3.3. France Machine Learning as a Service Market Outlook
      • 8.3.3.1. Market Size & Forecast
        • 8.3.3.1.1. By Value
      • 8.3.3.2. Market Share & Forecast
        • 8.3.3.2.1. By Component
        • 8.3.3.2.2. By Organization Size
        • 8.3.3.2.3. By Application
        • 8.3.3.2.4. By End-User
    • 8.3.4. Italy Machine Learning as a Service Market Outlook
      • 8.3.4.1. Market Size & Forecast
        • 8.3.4.1.1. By Value
      • 8.3.4.2. Market Share & Forecast
        • 8.3.4.2.1. By Component
        • 8.3.4.2.2. By Organization Size
        • 8.3.4.2.3. By Application
        • 8.3.4.2.4. By End-User
    • 8.3.5. Spain Machine Learning as a Service Market Outlook
      • 8.3.5.1. Market Size & Forecast
        • 8.3.5.1.1. By Value
      • 8.3.5.2. Market Share & Forecast
        • 8.3.5.2.1. By Component
        • 8.3.5.2.2. By Organization Size
        • 8.3.5.2.3. By Application
        • 8.3.5.2.4. By End-User

9. Asia Pacific Machine Learning as a Service Market Outlook

  • 9.1. Market Size & Forecast
    • 9.1.1. By Value
  • 9.2. Market Share & Forecast
    • 9.2.1. By Component
    • 9.2.2. By Organization Size
    • 9.2.3. By Application
    • 9.2.4. By End-User
    • 9.2.5. By Country
    • 9.2.6. Key Takeaways
  • 9.3. Asia Pacific: Country Analysis
    • 9.3.1. China Machine Learning as a Service Market Outlook
      • 9.3.1.1. Market Size & Forecast
        • 9.3.1.1.1. By Value
      • 9.3.1.2. Market Share & Forecast
        • 9.3.1.2.1. By Component
        • 9.3.1.2.2. By Organization Size
        • 9.3.1.2.3. By Application
        • 9.3.1.2.4. By End-User
    • 9.3.2. Japan Machine Learning as a Service Market Outlook
      • 9.3.2.1. Market Size & Forecast
        • 9.3.2.1.1. By Value
      • 9.3.2.2. Market Share & Forecast
        • 9.3.2.2.1. By Component
        • 9.3.2.2.2. By Organization Size
        • 9.3.2.2.3. By Application
        • 9.3.2.2.4. By End-User
    • 9.3.3. India Machine Learning as a Service Market Outlook
      • 9.3.3.1. Market Size & Forecast
        • 9.3.3.1.1. By Value
      • 9.3.3.2. Market Share & Forecast
        • 9.3.3.2.1. By Component
        • 9.3.3.2.2. By Organization Size
        • 9.3.3.2.3. By Application
        • 9.3.3.2.4. By End-User
    • 9.3.4. South Korea Machine Learning as a Service Market Outlook
      • 9.3.4.1. Market Size & Forecast
        • 9.3.4.1.1. By Value
      • 9.3.4.2. Market Share & Forecast
        • 9.3.4.2.1. By Component
        • 9.3.4.2.2. By Organization Size
        • 9.3.4.2.3. By Application
        • 9.3.4.2.4. By End-User
    • 9.3.5. Australia Machine Learning as a Service Market Outlook
      • 9.3.5.1. Market Size & Forecast
        • 9.3.5.1.1. By Value
      • 9.3.5.2. Market Share & Forecast
        • 9.3.5.2.1. By Component
        • 9.3.5.2.2. By Organization Size
        • 9.3.5.2.3. By Application
        • 9.3.5.2.4. By End-User

10. Middle East & Africa Machine Learning as a Service Market Outlook

  • 10.1. Market Size & Forecast
    • 10.1.1. By Value
  • 10.2. Market Share & Forecast
    • 10.2.1. By Component
    • 10.2.2. By Organization Size
    • 10.2.3. By Application
    • 10.2.4. By End-User
    • 10.2.5. By Country
    • 10.2.6. Key Takeaways
  • 10.3. Middle East & Africa: Country Analysis
    • 10.3.1. Saudi Arabia Machine Learning as a Service Market Outlook
      • 10.3.1.1. Market Size & Forecast
        • 10.3.1.1.1. By Value
      • 10.3.1.2. Market Share & Forecast
        • 10.3.1.2.1. By Component
        • 10.3.1.2.2. By Organization Size
        • 10.3.1.2.3. By Application
        • 10.3.1.2.4. By End-User
    • 10.3.2. UAE Machine Learning as a Service Market Outlook
      • 10.3.2.1. Market Size & Forecast
        • 10.3.2.1.1. By Value
      • 10.3.2.2. Market Share & Forecast
        • 10.3.2.2.1. By Component
        • 10.3.2.2.2. By Organization Size
        • 10.3.2.2.3. By Application
        • 10.3.2.2.4. By End-User
    • 10.3.3. South Africa Machine Learning as a Service Market Outlook
      • 10.3.3.1. Market Size & Forecast
        • 10.3.3.1.1. By Value
      • 10.3.3.2. Market Share & Forecast
        • 10.3.3.2.1. By Component
        • 10.3.3.2.2. By Organization Size
        • 10.3.3.2.3. By Application
        • 10.3.3.2.4. By End-User

11. South America Machine Learning as a Service Market Outlook

  • 11.1. Market Size & Forecast
    • 11.1.1. By Value
  • 11.2. Market Share & Forecast
    • 11.2.1. By Component
    • 11.2.2. By Organization Size
    • 11.2.3. By Application
    • 11.2.4. By End-User
    • 11.2.5. By Country
    • 11.2.6. Key Takeaways
  • 11.3. South America: Country Analysis
    • 11.3.1. Brazil Machine Learning as a Service Market Outlook
      • 11.3.1.1. Market Size & Forecast
        • 11.3.1.1.1. By Value
      • 11.3.1.2. Market Share & Forecast
        • 11.3.1.2.1. By Component
        • 11.3.1.2.2. By Organization Size
        • 11.3.1.2.3. By Application
        • 11.3.1.2.4. By End-User
    • 11.3.2. Argentina Machine Learning as a Service Market Outlook
      • 11.3.2.1. Market Size & Forecast
        • 11.3.2.1.1. By Value
      • 11.3.2.2. Market Share & Forecast
        • 11.3.2.2.1. By Component
        • 11.3.2.2.2. By Organization Size
        • 11.3.2.2.3. By Application
        • 11.3.2.2.4. By End-User
    • 11.3.3. Colombia Machine Learning as a Service Market Outlook
      • 11.3.3.1. Market Size & Forecast
        • 11.3.3.1.1. By Value
      • 11.3.3.2. Market Share & Forecast
        • 11.3.3.2.1. By Component
        • 11.3.3.2.2. By Organization Size
        • 11.3.3.2.3. By Application
        • 11.3.3.2.4. By End-User

12. Market Dynamics

  • 12.1. Drivers
    • 12.1.1. Increase demand for cloud computing
    • 12.1.2. Growth associate with cognitive computing & AI
    • 12.1.3. Rise in adoption of analytics solutions
  • 12.2. Challenges
    • 12.2.1. Lack of skilled resources
    • 12.2.2. Lacking infrastructure

13. Market Trends and Developments

  • 13.1. Increasing customer facing activities
  • 13.2. Smarter back office & operations
  • 13.3. Growing use of machine learning in retail sector
  • 13.4. Mergers & Acquisitions
  • 13.5. Exponential growth of big data

14. Company Profiles

  • 14.1. Google Inc
    • 14.1.1. Company Overview
    • 14.1.2. Product Portfolio
    • 14.1.3. SWOT Analysis
    • 14.1.4. Key Personals
    • 14.1.5. Recent Developments/Updates
  • 14.2. SAS Institute Inc
    • 14.2.1. Company Overview
    • 14.2.2. Product Portfolio
    • 14.2.3. SWOT Analysis
    • 14.2.4. Key Personals
    • 14.2.5. Recent Developments/Updates
  • 14.3. Fair Isaac Corporation
    • 14.3.1. Company Overview
    • 14.3.2. Product Portfolio
    • 14.3.3. SWOT Analysis
    • 14.3.4. Key Personals
    • 14.3.5. Recent Developments/Updates
  • 14.4. Hewlett Packard Enterprise Development LP
    • 14.4.1. Company Overview
    • 14.4.2. Product Portfolio
    • 14.4.3. SWOT Analysis
    • 14.4.4. Key Personals
    • 14.4.5. Recent Developments/Updates
  • 14.5. Yottamine Analytics Inc.
    • 14.5.1. Company Overview
    • 14.5.2. Product Portfolio
    • 14.5.3. SWOT Analysis
    • 14.5.4. Key Personals
    • 14.5.5. Recent Developments/Updates
  • 14.6. Amazon Web Services
    • 14.6.1. Company Overview
    • 14.6.2. Product Portfolio
    • 14.6.3. SWOT Analysis
    • 14.6.4. Key Personals
    • 14.6.5. Recent Developments/Updates
  • 14.7. BigML, Inc.
    • 14.7.1. Company Overview
    • 14.7.2. Product Portfolio
    • 14.7.3. SWOT Analysis
    • 14.7.4. Key Personals
    • 14.7.5. Recent Developments/Updates
  • 14.8. Microsoft Corporation
    • 14.8.1. Company Overview
    • 14.8.2. Product Portfolio
    • 14.8.3. SWOT Analysis
    • 14.8.4. Key Personals
    • 14.8.5. Recent Developments/Updates
  • 14.9. IBM Corporation
    • 14.9.1. Company Overview
    • 14.9.2. Product Portfolio
    • 14.9.3. SWOT Analysis
    • 14.9.4. Key Personals
    • 14.9.5. Recent Developments/Updates
  • 14.10. Broadcom Corporation
    • 14.10.1. Company Overview
    • 14.10.2. Product Portfolio
    • 14.10.3. SWOT Analysis
    • 14.10.4. Key Personals
    • 14.10.5. Recent Developments/Updates

15. Strategic Recommendations

  • 15.1. Use sophisticated algorithms for data utilizing
  • 15.2. Use customer churn modelling

16. About Us & Disclaimer