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機器學習市場 - 全球行業規模、佔有率、趨勢、機會和預測。 2018-2028年按組件、按企業規模、按部署、按終端用戶、按地區分類。
市場調查報告書
商品編碼
1289669

機器學習市場 - 全球行業規模、佔有率、趨勢、機會和預測。 2018-2028年按組件、按企業規模、按部署、按終端用戶、按地區分類。

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個工作天內

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簡介目錄

在2022-2028年的預測期內，全球機器學習市場預計將以強勁的速度成長。技術創新是全球機器學習市場成長背後的關鍵力量。機器學習（ML）中的人工智慧（AI）使電腦程序員能夠在沒有明確訓練的情況下更準確地預測結果。人工智慧和機器學習是發展和IT企業的最新界限。機器學習是一個研究領域，專注於分析和開發"學習"過程和方法，利用數據來提高特定任務的效率。

擴大採用基於雲端的服務和進行有效輸出的能力

海量的數據可以通過機器學習來審查，它可以識別人們會忽視的趨勢和模式。例如，像亞馬遜這樣的電子商務網站，了解客戶的瀏覽模式和過去的購買行為，使其能夠為客戶提供適當的商品、折扣和提醒。此外，機器學習也被雲端計算平台ServiceNow部分使用。該組織提供工作流程軟體，採用機器學習來協助其客戶盡可能多地將繁瑣的程序自動化，並確保工作人員高效工作。

自動駕駛汽車和多個處理數據集的最新趨勢

公司正在使用這種開源的人工智慧庫來發展他們的機器學習能力。例如，TensorFlow是組織用來建立Java項目、數據流圖和各種應用程式的庫。 Java的API也是存在的。例如，埃森哲諮詢公司和專業服務公司正在使用基於機器學習的技術，其市場容量為2290億美元。由於這個市場預計在預測期內會成長。

許多現代移動設備可以在用戶進行某種活動時自主識別，如騎自行車或跑步。現在，新手機器學習工程師利用由幾個人的健身活動記錄組成的數據集，這些記錄是用配備慣性感測器的移動設備獲得的，用來練習這類項目。此外，學生們正在使用能夠精確預測未來行動的分類模型。由於這個原因，在預測期內，數據集市場對機器學習的採用可能會增加。

汽車領域也正在引入ML。例如，美國跨國公司特斯拉宣布推出自動駕駛。雖然他們產生了爭議，但自動駕駛汽車構成了機器學習中引入的最顯著的進步之一。在預測期內，這一市場預計將以較高的複合年成長率成長。

由於機器學習在機器人中的整合，機器學習市場也在擴大。例如，根據統計年鑑"世界機器人"，2018年美國的機器人安裝達到了一個新的高度。支持他們使用使用PID算法的Line Follower機器人，由於這一點，全球機器學習市場在未來正在擴大。

缺少熟練的員工

然而，大多數組織在將機器學習整合到其業務流程中時的主要困難是缺乏具有分析才能的合格工人，而且更需要那些能夠關注分析材料的人。

市場參與者

全球機器學習市場的主要市場參與者有：亞馬遜網路服務有限公司、百度公司、多米諾數據實驗室公司、微軟公司、谷歌公司、阿爾卑斯數據公司、IBM公司、SAP SE、英特爾公司和SAS研究所公司。

最近的發展

  • 目前，印度的NITI Aayog正在研究使用DNN模型對糖尿病和心臟風險進行早期診斷和識別。美國食品和藥物管理局也正在製定一個法律框架，以便在醫療保健領域利用人工智慧和機器智慧。
  • Nvidia提供高階影片遊戲圖形最好，但該公司在人工智慧和機器學習方面的賭博近年來已開始得到回報。
  • 總部位於倫敦的Wayve公司在2022年1月融資2億美元。因此，企業將更有能力訓練和建立能夠處理挑戰性駕駛情況的人工智慧。
  • 埃森哲是全球領先的諮詢機構和技術權威，經常協助企業使用技術來改變其營運。機器學習是埃森哲的各種專業領域之一。

可用的客製化服務

全球機器學習市場報告根據給定的市場數據，TechSci Research根據公司的具體需求提供客製化服務。該報告有以下客製化選項：

公司資訊

其他市場參與者（最多5家）的詳細分析和簡介。

目錄

第一章：服務概述

  • 市場定義
  • 市場的範圍
  • 涵蓋的市場
  • 研究涵蓋的年份
  • 關鍵的市場細分

第二章：研究方法

  • 基準方法
  • 主要行業合作夥伴
  • 主要協會和二級來源
  • 預測方法
  • 數據三角測量和驗證
  • 假設和限制

第三章：執行摘要

第四章：客戶的聲音

第五章：全球機器學習市場

  • 市場規模和預測
    • 按價值
  • 市場佔有率和預測
    • 按組件（服務和解決方案）分類
    • 按企業規模（中小企業和大型企業）分類
    • 按部署（雲端和企業內部）分類
    • 按終端用戶（醫療、零售、IT和電信、汽車和運輸、廣告和媒體、BFSI、政府和國防以及其他）分類
    • 按地區
  • 按公司分類(2022年)
  • 市場地圖

第六章：北美機器學習市場展望

  • 市場規模和預測
    • 按價值
  • 市場佔有率和預測
    • 按組件分類
    • 按企業規模分類
    • 按部署情況
    • 按終端用途
    • 按國家分類
  • 北美洲：國家分析
    • 美國
    • 美國
    • 墨西哥

第7章：亞太地區機器學習市場前景

  • 市場規模和預測
    • 按價值
  • 市場佔有率與預測
    • 按組件分類
    • 按企業規模
    • 按部署情況
    • 按終端用途
    • 按國家分類
  • 亞太地區：國家分析
    • 中國
    • 印度
    • 日本
    • 韓國
    • 澳大利亞
    • 新加坡
    • 馬來西亞

第8章：歐洲機器學習市場前景

  • 市場規模和預測
    • 按價值
  • 市場佔有率與預測
    • 按組件
    • 按企業規模
    • 按部署情況
    • 按終端用途
    • 按國家分類
  • 歐洲：國家分析
    • 德國
    • 英國
    • 法國
    • 俄羅斯
    • 西班牙
    • 波蘭
    • 義大利
    • 丹麥

第九章：南美機器學習市場展望

  • 市場規模和預測
    • 按價值
  • 市場佔有率與預測
    • 按組件分類
    • 按企業規模分類
    • 按部署情況
    • 按終端用途
    • 按國家分類
  • 南美洲：國家分析
    • 巴西
    • 阿根廷
    • 哥倫比亞
    • 秘魯
    • 智利

第十章：中東和非洲機器學習市場展望

  • 市場規模和預測
    • 按價值
  • 市場佔有率與預測
    • 按組件分類
    • 按企業規模分類
    • 按部署情況
    • 按終端用途
    • 按國家分類
  • 中東和非洲：國家分析
    • 沙烏地阿拉伯
    • 南非
    • 阿拉伯聯合大公國
    • 土耳其

第十一章：市場動態

  • 驅動力
  • 挑戰

第十二章：市場趨勢與發展

第十三章：公司簡介

  • 亞馬遜網路服務有限公司
    • 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
  • 多米諾數據實驗室公司
    • Business Overview
    • Key Revenue and Financials (If Available)
    • Recent Developments
    • Key Personnel
    • Key Product/Services
  • 微軟公司
    • 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
  • 阿爾卑斯數據公司
    • 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
  • 英特爾公司
    • 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：戰略建議

第15章關於出版商,免責事項

簡介目錄
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