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机器学习市场 - 全球行业规模、份额、趋势、机会和预测。2018-2028年按组件、按企业规模、按部署、按终端用户、按地区划分。
市场调查报告书
商品编码
1289669

机器学习市场 - 全球行业规模、份额、趋势、机会和预测。2018-2028年按组件、按企业规模、按部署、按终端用户、按地区划分。

Machine Learning Market - Global Industry Size, Share, Trends, Opportunity, and Forecast. 2018-2028 Segmented By Component, By Enterprises Size, By Deployment, By End-User, By Region
出版日期: | 出版商: TechSci Research | 英文 116 Pages | 商品交期: 2-3个工作天内

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简介目录

在2022-2028年的预测期内，全球机器学习市场预计将以强劲的速度增长。技术创新是全球机器学习市场增长背后的关键力量。机器学习（ML）中的人工智能（AI）使计算机程序员能够在没有明确训练的情况下更准确地预测结果。人工智能和机器学习是发展和IT企业的最新界限。机器学习是一个研究领域，专注于分析和开发 "学习 "过程和方法，利用数据来提高特定任务的效率。

越来越多地采用基于云的服务和进行有效输出的能力

海量的数据可以通过机器学习来审查，它可以识别人们会忽视的趋势和模式。例如，像亚马逊这样的电子商务网站，了解客户的浏览模式和过去的购买行为，使其能够为客户提供适当的商品、折扣和提醒。此外，机器学习也被云计算平台ServiceNow部分使用。该组织提供工作流程软件，采用机器学习来协助其客户尽可能多地将繁琐的程序自动化，并确保工作人员高效工作。

自动驾驶汽车和多个处理数据集的最新趋势

公司正在使用这种开源的人工智能库来发展他们的机器学习能力。例如，TensorFlow是组织用来建立Java项目、数据流图和各种应用程序的库。Java的API也是存在的。例如，埃森哲咨询公司和专业服务公司正在使用基于机器学习的技术，其市场容量为2290亿美元。由于这个市场预计在预测期内会增长。

许多现代移动设备可以在用户进行某种活动时自主识别，如骑自行车或跑步。现在，新手机器学习工程师利用由几个人的健身活动记录组成的数据集，这些记录是用配备惯性传感器的移动设备获得的，用来练习这类项目。此外，学生们正在使用能够精确预测未来行动的分类模型。由于这个原因，在预测期内，数据集市场对机器学习的采用可能会增加。

汽车领域也正在引入ML。例如，美国跨国公司特斯拉宣布推出自动驾驶。虽然他们产生了争议，但自动驾驶汽车构成了机器学习中引入的最显著的进步之一。在预测期内，这一市场预计将以较高的复合年增长率增长。

由于机器学习在机器人中的整合，机器学习市场也在扩大。例如，根据统计年鉴 "世界机器人"，2018年美国的机器人安装达到了一个新的高度。支持他们使用使用PID算法的Line Follower机器人，由于这一点，全球机器学习市场在未来正在扩大。

缺少熟练的员工

然而，大多数组织在将机器学习整合到其业务流程中时的主要困难是缺乏具有分析才能的合格工人，而且更需要那些能够关注分析材料的人。

市场参与者

全球机器学习市场的主要市场参与者有：亚马逊网络服务有限公司、百度公司、多米诺数据实验室公司、微软公司、谷歌公司、阿尔卑斯数据公司、IBM公司、SAP SE、英特尔公司和SAS研究所公司。

最近的发展

  • 目前，印度的NITI Aayog正在研究使用DNN模型对糖尿病和心脏风险进行早期诊断和识别。美国食品和药物管理局也正在制定一个法律框架，以便在医疗保健领域利用人工智能和机器智能。
  • Nvidia提供高端视频游戏图形最好，但该公司在人工智能和机器学习方面的赌博近年来已开始得到回报。
  • 总部位于伦敦的Wayve公司在2022年1月融资2亿美元。因此，企业将更有能力训练和建立能够处理挑战性驾驶情况的人工智能。
  • 埃森哲是全球领先的咨询机构和技术权威，经常协助企业使用技术来改变其运营。机器学习是埃森哲的各种专业领域之一。

可用的定制服务

全球机器学习市场报告根据给定的市场数据，TechSci Research根据公司的具体需求提供定制服务。该报告有以下定制选项：

公司信息

其他市场参与者（最多5家）的详细分析和简介。

目录

第一章：服务概述

  • 市场定义
  • 市场的范围
  • 涵盖的市场
  • 研究考虑的年份
  • 关键的市场细分

第二章：研究方法

  • 基准方法
  • 主要行业合作伙伴
  • 主要协会和二级来源
  • 预测方法
  • 数据三角测量和验证
  • 假设和限制

第三章：执行摘要

第四章：客户的声音

第五章：全球机器学习市场

  • 市场规模和预测
    • 按价值
  • 市场份额和预测
    • 按组件（服务和解决方案）分类
    • 按企业规模（中小企业和大型企业）分类
    • 按部署（云和企业内部）分类
    • 按终端用户（医疗、零售、IT和电信、汽车和运输、广告和媒体、BFSI、政府和国防以及其他）分类
    • 按地区
  • 按公司分类 (2022年)
  • 市场地图

第六章：北美机器学习市场展望

  • 市场规模和预测
    • 按价值
  • 市场份额和预测
    • 按组件分类
    • 按企业规模分类
    • 按部署情况
    • 按终端用途
    • 按国家分类
  • 北美洲：国家分析
    • 美国
    • 美国
    • 墨西哥

第7章 ：亚太地区机器学习市场前景

  • 市场规模和预测
    • 按价值
  • 市场份额与预测
    • 按组件分类
    • 按企业规模
    • 按部署情况
    • 按终端用途
    • 按国家分类
  • 亚太地区：国家分析
    • 中国
    • 印度
    • 日本
    • 韩国
    • 澳大利亚
    • 新加坡
    • 马来西亚

第8章：欧洲机器学习市场前景

  • 市场规模和预测
    • 按价值
  • 市场份额与预测
    • 按组件
    • 按企业规模
    • 按部署情况
    • 按终端用途
    • 按国家分类
  • 欧洲：国家分析
    • 德国
    • 英国
    • 法国
    • 俄罗斯
    • 西班牙
    • 波兰
    • 意大利
    • 丹麦

第九章：南美机器学习市场展望

  • 市场规模和预测
    • 按价值
  • 市场份额与预测
    • 按组件分类
    • 按企业规模分类
    • 按部署情况
    • 按终端用途
    • 按国家分类
  • 南美洲：国家分析
    • 巴西
    • 阿根廷
    • 哥伦比亚
    • 秘鲁
    • 智利

第十章：中东和非洲机器学习市场展望

  • 市场规模和预测
    • 按价值
  • 市场份额与预测
    • 按组件分类
    • 按企业规模分类
    • 按部署情况
    • 按终端用途
    • 按国家分类
  • 中东和非洲：国家分析
    • 沙特阿拉伯
    • 南非
    • 阿联酋
    • 土耳其

第十一章 ：市场动态

  • 驱动力
  • 挑战

第十二章 ：市场趋势与发展

第十三章 ：公司简介

  • 亚马逊网络服务有限公司
    • Business Overview
    • Key Revenue and Financials (If Available)
    • Recent Developments
    • Key Personnel
    • Key Product/Services
  • 百度，公司。
    • Business Overview
    • Key Revenue and Financials (If Available)
    • Recent Developments
    • Key Personnel
    • Key Product/Services
  • 多米诺数据实验室公司
    • Business Overview
    • Key Revenue and Financials (If Available)
    • Recent Developments
    • Key Personnel
    • Key Product/Services
  • 微软公司
    • Business Overview
    • Key Revenue and Financials (If Available)
    • Recent Developments
    • Key Personnel
    • Key Product/Services
  • 谷歌公司
    • Business Overview
    • Key Revenue and Financials (If Available)
    • Recent Developments
    • Key Personnel
    • Key Product/Services
  • 阿尔卑斯数据公司
    • Business Overview
    • Key Revenue and Financials (If Available)
    • Recent Developments
    • Key Personnel
    • Key Product/Services
  • IBM公司
    • Business Overview
    • Key Revenue and Financials (If Available)
    • Recent Developments
    • Key Personnel
    • Key Product/Services
  • SAP SE
    • Business Overview
    • Key Revenue and Financials (If Available)
    • Recent Developments
    • Key Personnel
    • Key Product/Services
  • 英特尔公司
    • Business Overview
    • Key Revenue and Financials (If Available)
    • Recent Developments
    • Key Personnel
    • Key Product/Services
  • SAS研究所公司
    • Business Overview
    • Key Revenue and Financials (If Available)
    • Recent Developments
    • Key Personnel
    • Key Product/Services

第14章：战略建议

第15章 调査会社について・免除责任事项

简介目录
Product Code: 14561

The Global Machine Learning Market is anticipated to grow at a robust pace in the forecast period 2022-2028. Technological innovation is the key strength behind the growth of the global machine-learning market. Artificial intelligence (AI) in machine learning (ML) enables computer programmers to forecast outcomes more accurately without being expressly trained. AI and machine learning are the newest boundaries for development and IT enterprises. Machine learning is an area of research focused on analyzing and developing "learning" processes and methods that use data to enhance efficiency on a given set of tasks.

Rising adoption of cloud-based services & ability to perform effectual output

Massive amounts of data can be reviewed by machine learning, which can identify trends and patterns that people would overlook. For instance, an e-commerce site like Amazon, knowing its customers' browsing patterns and past purchases, enables it to offer them the appropriate goods, discounts, and reminders. Furthermore, machine learning is used in part by ServiceNow, a cloud computing platform. The organization, which provides workflow software, employs machine learning to assist its clients in automating as many tedious procedures as possible and ensuring that staff members are working efficiently.

The ability to perform operations without involving human involvement, improvements in data center capabilities, and high computing power contribute to the technology's rise to prominence. Additionally, the market is expanding as a result of the quick adoption of cloud-based technologies in numerous sectors, such as Virtual services like software as a service (SaaS), platforms as a service (PaaS), and infrastructure as a service.

Machine Learning allows the identification of failures and their mitigation, directly affecting the standard and advancement of the process. Making errors enables process improvement. In addition to the ability for mistake and failure prevention, ML has stock prediction algorithms. Models built from data can forecast when an error may happen, enabling preventative measures to stop it from happening. This will likely cause the market to grow throughout the projected period.

Latest Trend of Self-Driving Vehicles and Multiple Handle Datasets

Companies are using this open-source artificial intelligence library to develop their machine-learning capabilities. For Instance, TensorFlow is library organizations use to build Java projects, data flow graphs, and various applications. APIs for Java are also present. For instance, Accenture Consultancy and professional services firms are using machine learning-based technologies with a market cap of USD 229 billion. Due to this market is expected to grow in the forecast period.

Many modern mobile devices can recognize autonomously when a user performs a certain activity, like cycling or running. Nowadays, novice machine learning engineers utilize a dataset that comprises fitness activity records for a few people that were acquired using mobile devices equipped with inertial sensors to practice with this sort of project. Furthermore, students are using categorization models that can precisely forecast future actions. Due to this, the adoption of machine learning in the datasets market is likely to increase in the forecast period.

ML is also being introduced in the automotive sector. For instance, Tesla, an American multinational company, announced the launch of self-driving. Although they have generated controversy, self-driving cars constitute one of the most remarkable advancements introduced in machine learning. This market is expected to grow with a high CAGR in the forecast period.

The machine-learning market has also expanded due to the integration of machine learning-in robots. For instance, Robot installations reached a new height in the United States in 2018, according to the statistics yearbook "World Robotics." Supporting they are using Line Follower Robot Using PID Algorithm due to which the Global machine learning market is expanding in the future.

Lack of skilled employees

However, the main difficulty most organizations have when integrating machine learning into their business processes is a lack of qualified workers with analytical talent, and there is an even greater need for those who can keep an eye on analytical material.

Market Segmentation

The Global Machine Learning Market is segmented into component, enterprise size, deployment, end-user, regional distribution, and competitive landscape. Based on components, the market is segmented into Services & Solutions. Based on enterprises' size, the market is divided into SMEs and large enterprises. Based on deployment, the market is divided into cloud and on-premises. Based on end-user, the market is divided into healthcare, retailer, it & telecom, automotive and transports, advertising & media, BFSI, government and defense, and others.

Market player

The main market players in the Global Machine Learning Market are Amazon Web Services, Inc., Baidu, Inc, Domino Data Lab, Inc, Microsoft Corporation, Google, Inc, Alpine Data, IBM Corporation, SAP SE, Intel Corporation, and SAS Institute Inc.

Recent Developments

  • The use of DNN models for the early diagnosis and identification of diabetes and cardiac risk is now being worked on by NITI Aayog in India. The FDA is also developing a legal framework for utilizing AI and machine intelligence in the healthcare sector.
  • Nvidia provides high-end video game graphics best, but the company's gamble on AI and machine learning has begun to pay off in recent years.
  • The London-based firm Wayve raised USD200 million in January 2022. As a result, enterprises will be better equipped to train and build artificial intelligence capable of handling challenging driving situations.
  • Accenture is a leading worldwide consulting organization and technology authority that frequently assists businesses in using technology to alter their operations. Machine learning is one of Accenture's various specialties.

Report Scope

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

Machine Learning Market, By Component:

  • Services
  • Solutions

Machine Learning Market, By Enterprises Size:

  • SMEs
  • Large enterprises

Machine Learning Market, By Deployment:

  • Cloud
  • On-premises

Machine Learning Market, By End-user:

  • Healthcare
  • Retailer
  • IT & telecom
  • Automotive and Transports
  • Advertising & Media
  • BFSI
  • Government and Defense
  • Others

Machine Learning Market, By Region:

  • North America
    • United States
    • Mexico
    • Canada
  • Asia-Pacific
    • India
    • Japan
    • South Korea
    • Australia
    • Singapore
    • Malaysia
    • China
  • Europe
    • Germany
    • United Kingdom
    • France
    • Italy
    • Spain
    • Poland
    • Denmark
  • South America
    • Brazil
    • Argentina
    • Colombia
    • Peru
    • Chile
  • Middle East
    • Saudi Arabia
    • South Africa
    • UAE
    • Iraq
    • Turkey

Competitive Landscape

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

Available Customizations

Global Machine Learning Market report with the given market data, TechSci 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

2. Research Methodology

3. Impact of COVID-19 Global Machine Learning Market

4. Executive Summary

5. Voice of Customers

6. Global Machine Learning Market

  • 6.1. Market Size & Forecast
    • 6.1.1. By Value
  • 6.2. Market Share & Forecast
    • 6.2.1. By Component (Services & Solutions)
    • 6.2.2. By Enterprises Size (SMEs and Large enterprises)
    • 6.2.3. By Deployment (Cloud and On-premises)
    • 6.2.4. By End-User (Healthcare, Retailer, IT & Telecom, Automotive and Transports, Advertising & Media, BFSI, Government and Defense and Others)
    • 6.2.5. By Region
  • 6.3. By Company (2022)
  • 6.4. Market Map

7. North America Machine Learning 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 Enterprises Size
    • 7.2.3. By Deployment
    • 7.2.4. By End-Use
    • 7.2.5. By Country
  • 7.3. North America: Country Analysis
    • 7.3.1. United States Machine Learning 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 Enterprises Size
        • 7.3.1.2.3. By Deployment
        • 7.3.1.2.4. By End-Use
    • 7.3.2. Canada Machine Learning 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 Enterprises Size
        • 7.3.2.2.3. By Deployment
        • 7.3.2.2.4. By End-Use
    • 7.3.3. Mexico Machine Learning 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 Enterprises Size
        • 7.3.3.2.3. By Deployment
        • 7.3.3.2.4. By End-Use

8. Asia-Pacific Machine Learning 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 Enterprises Size
    • 8.2.3. By Deployment
    • 8.2.4. By End-Use
    • 8.2.5. By Country
  • 8.3. Asia-Pacific: Country Analysis
    • 8.3.1. China Machine Learning 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 Enterprises Size
        • 8.3.1.2.3. By Deployment
        • 8.3.1.2.4. By End-Use
    • 8.3.2. India Machine Learning 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 Enterprises Size
        • 8.3.2.2.3. By Deployment
        • 8.3.2.2.4. By End-Use
    • 8.3.3. Japan Machine Learning 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 Enterprises Size
        • 8.3.3.2.3. By Deployment
        • 8.3.3.2.4. By End-Use
    • 8.3.4. South Korea Machine Learning 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 Enterprises Size
        • 8.3.4.2.3. By Deployment
        • 8.3.4.2.4. By End-Use
    • 8.3.5. Australia Machine Learning 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 Enterprises Size
        • 8.3.5.2.3. By Deployment
        • 8.3.5.2.4. By End-Use
    • 8.3.6. Singapore Machine Learning Market Outlook
      • 8.3.6.1. Market Size & Forecast
        • 8.3.6.1.1. By Value
      • 8.3.6.2. Market Share & Forecast
        • 8.3.6.2.1. By Component
        • 8.3.6.2.2. By Enterprises Size
        • 8.3.6.2.3. By Deployment
        • 8.3.6.2.4. By End-Use
    • 8.3.7. Malaysia Machine Learning Market Outlook
      • 8.3.7.1. Market Size & Forecast
        • 8.3.7.1.1. By Value
      • 8.3.7.2. Market Share & Forecast
        • 8.3.7.2.1. By Component
        • 8.3.7.2.2. By Enterprises Size
        • 8.3.7.2.3. By Deployment
        • 8.3.7.2.4. By End-Use

9. Europe Machine Learning 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 Enterprises Size
    • 9.2.3. By Deployment
    • 9.2.4. By End-Use
    • 9.2.5. By Country
  • 9.3. Europe: Country Analysis
    • 9.3.1. Germany Machine Learning 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 Enterprises Size
        • 9.3.1.2.3. By Deployment
        • 9.3.1.2.4. By End-Use
    • 9.3.2. United Kingdom Machine Learning 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 Enterprises Size
        • 9.3.2.2.3. By Deployment
        • 9.3.2.2.4. By End-Use
    • 9.3.3. France Machine Learning 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 Enterprises Size
        • 9.3.3.2.3. By Deployment
        • 9.3.3.2.4. By End-Use
    • 9.3.4. Russia Machine Learning 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 Enterprises Size
        • 9.3.4.2.3. By Deployment
        • 9.3.4.2.4. By End-Use
    • 9.3.5. Spain Machine Learning 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 Enterprises Size
        • 9.3.5.2.3. By Deployment
        • 9.3.5.2.4. By End-Use
    • 9.3.6. Poland Machine Learning Market Outlook
      • 9.3.6.1. Market Size & Forecast
        • 9.3.6.1.1. By Value
      • 9.3.6.2. Market Share & Forecast
        • 9.3.6.2.1. By Component
        • 9.3.6.2.2. By Enterprises Size
        • 9.3.6.2.3. By Deployment
        • 9.3.6.2.4. By End-Use
    • 9.3.7. Italy Machine Learning Market Outlook
      • 9.3.7.1. Market Size & Forecast
        • 9.3.7.1.1. By Value
      • 9.3.7.2. Market Share & Forecast
        • 9.3.7.2.1. By Component
        • 9.3.7.2.2. By Enterprises Size
        • 9.3.7.2.3. By Deployment
        • 9.3.7.2.4. By End-Use
    • 9.3.8. Denmark Machine Learning Market Outlook
      • 9.3.8.1. Market Size & Forecast
        • 9.3.8.1.1. By Value
      • 9.3.8.2. Market Share & Forecast
        • 9.3.8.2.1. By Component
        • 9.3.8.2.2. By Enterprises Size
        • 9.3.8.2.3. By Deployment
        • 9.3.8.2.4. By End-Use

10. South America Machine Learning 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 Enterprises Size
    • 10.2.3. By Deployment
    • 10.2.4. By End-Use
    • 10.2.5. By Country
  • 10.3. South America: Country Analysis
    • 10.3.1. Brazil Machine Learning 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 Enterprises Size
        • 10.3.1.2.3. By Deployment
        • 10.3.1.2.4. By End-Use
    • 10.3.2. Argentina Machine Learning 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 Enterprises Size
        • 10.3.2.2.3. By Deployment
        • 10.3.2.2.4. By End-Use
    • 10.3.3. Colombia Machine Learning 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 Enterprises Size
        • 10.3.3.2.3. By Deployment
        • 10.3.3.2.4. By End-Use
    • 10.3.4. Peru Machine Learning Market Outlook
      • 10.3.4.1. Market Size & Forecast
        • 10.3.4.1.1. By Value
      • 10.3.4.2. Market Share & Forecast
        • 10.3.4.2.1. By Component
        • 10.3.4.2.2. By Enterprises Size
        • 10.3.4.2.3. By Deployment
        • 10.3.4.2.4. By End-Use
    • 10.3.5. Chile Machine Learning Market Outlook
      • 10.3.5.1. Market Size & Forecast
        • 10.3.5.1.1. By Value
      • 10.3.5.2. Market Share & Forecast
        • 10.3.5.2.1. By Component
        • 10.3.5.2.2. By Enterprises Size
        • 10.3.5.2.3. By Deployment
        • 10.3.5.2.4. By End-Use

11. Middle East & Africa Machine Learning 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 Enterprises Size
    • 11.2.3. By Deployment
    • 11.2.4. By End-Use
    • 11.2.5. By Country
  • 11.3. Middle East & Africa: Country Analysis
    • 11.3.1. Saudi Arabia Machine Learning 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 Enterprises Size
        • 11.3.1.2.3. By Deployment
        • 11.3.1.2.4. By End-Use
    • 11.3.2. South Africa Machine Learning 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 Enterprises Size
        • 11.3.2.2.3. By Deployment
        • 11.3.2.2.4. By End-Use
    • 11.3.3. UAE Machine Learning 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 Enterprises Size
        • 11.3.3.2.3. By Deployment
        • 11.3.3.2.4. By End-Use
    • 11.3.4. Israel Machine Learning Market Outlook
      • 11.3.4.1. Market Size & Forecast
        • 11.3.4.1.1. By Value
      • 11.3.4.2. Market Share & Forecast
        • 11.3.4.2.1. By Component
        • 11.3.4.2.2. By Enterprises Size
        • 11.3.4.2.3. By Deployment
        • 11.3.4.2.4. By End-Use
    • 11.3.5. Turkey Machine Learning Market Outlook
      • 11.3.5.1. Market Size & Forecast
        • 11.3.5.1.1. By Value
      • 11.3.5.2. Market Share & Forecast
        • 11.3.5.2.1. By Component
        • 11.3.5.2.2. By Enterprises Size
        • 11.3.5.2.3. By Deployment
        • 11.3.5.2.4. By End-Use

12. Market Dynamics

  • 12.1. Drivers
  • 12.2. Challenges

13. Market Trends & Developments

14. Company Profiles

  • 14.1. Amazon Web Services, Inc.
    • 14.1.1. Business Overview
    • 14.1.2. Key Revenue and Financials
    • 14.1.3. Recent Developments
    • 14.1.4. Key Personnel
    • 14.1.5. Key Product/Services
  • 14.2. Baidu, Inc.
    • 14.2.1. Business Overview
    • 14.2.2. Key Revenue and Financials
    • 14.2.3. Recent Developments
    • 14.2.4. Key Personnel
    • 14.2.5. Key Product/Services
  • 14.3. Domino Data Lab, Inc.
    • 14.3.1. Business Overview
    • 14.3.2. Key Revenue and Financials
    • 14.3.3. Recent Developments
    • 14.3.4. Key Personnel
    • 14.3.5. Key Product/Services
  • 14.4. Microsoft Corporation
    • 14.4.1. Business Overview
    • 14.4.2. Key Revenue and Financials
    • 14.4.3. Recent Developments
    • 14.4.4. Key Personnel
    • 14.4.5. Key Product/Services
  • 14.5. Google, Inc.
    • 14.5.1. Business Overview
    • 14.5.2. Key Revenue and Financials
    • 14.5.3. Recent Developments
    • 14.5.4. Key Personnel
    • 14.5.5. Key Product/Services
  • 14.6. Alpine Data
    • 14.6.1. Business Overview
    • 14.6.2. Key Revenue and Financials
    • 14.6.3. Recent Developments
    • 14.6.4. Key Personnel
    • 14.6.5. Key Product/Services
  • 14.7. IBM Corporation
    • 14.7.1. Business Overview
    • 14.7.2. Key Revenue and Financials
    • 14.7.3. Recent Developments
    • 14.7.4. Key Personnel
    • 14.7.5. Key Product/Services
  • 14.8. SAP SE
    • 14.8.1. Business Overview
    • 14.8.2. Key Revenue and Financials
    • 14.8.3. Recent Developments
    • 14.8.4. Key Personnel
    • 14.8.5. Key Product/Services
  • 14.9. Intel Corporation
    • 14.9.1. Business Overview
    • 14.9.2. Key Revenue and Financials
    • 14.9.3. Recent Developments
    • 14.9.4. Key Personnel
    • 14.9.5. Key Product/Services
  • 14.10. SAS Institute Inc.
    • 14.10.1. Business Overview
    • 14.10.2. Key Revenue and Financials
    • 14.10.3. Recent Developments
    • 14.10.4. Key Personnel
    • 14.10.5. Key Product/Services

15. Strategic Recommendations

16. About Us & Disclaimer