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機器學習營運市場：按組件、部署、組織規模和最終用戶 - 2025-2030 年全球預測

Machine Learning Operations Market by Component (Services, Software), Deployment (Cloud, On-Premise), Organization Size, End-User - Global Forecast 2025-2030
出版日期: | 出版商: 360iResearch | 英文 197 Pages | 商品交期: 最快1-2個工作天內

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2023年機器學習營運市場的市場規模為32.4億美元，預計2024年將達到44.1億美元，複合年成長率為36.22%，預計到2030年將達到282.6億美元。

機器學習營運 (MLOps) 是資料科學中一個快速新興的領域，它將 DevOps 原則與機器學習結合，以簡化機器學習生命週期。這項需求源自於生產環境中部署、監控和維護機器學習模型的複雜性日益增加。隨著人工智慧在醫療保健、金融和零售等行業的應用不斷增加，MLOps 可確保 ML 模型的營運效率、可重複性和可擴展性。 MLOps 平台和工具透過自動化資料攝取、模型訓練、檢驗和部署等流程來最佳化工作流程並減少瓶頸。該市場的主要推動因素是企業擴大採用人工智慧、提高模型準確性的需求以及由於巨量資料和雲端運算的顯著成長而導致的可擴展性需求的增加。隨著各行業尋求利用先進的人工智慧技術增強決策和預測能力，預計它將獲得關注。然而，整合複雜性、初始成本高和缺乏熟練人員等挑戰可能會阻礙市場成長。此外，有關資料隱私的安全問題和合規問題仍然存在，為全面實施造成障礙。自動化機器學習、即時模型監控以及開發有助於與現有 IT 環境無縫整合的框架等領域都存在機會。鼓勵公司投資開發混合雲端平台，並加強資料科學家和 IT 營運人員之間的協作，以利用 MLOps。創新者應專注於改善開放原始碼解決方案並開發強大的管治框架，以推動跨產業更廣泛的採用。市場競爭激烈，但企業正在優先考慮敏捷性和效率，以改變先進分析在當今動態市場格局中提供見解和驅動資料主導決策的方式，其中之一是人工智慧營運的現代化。

主要市場統計
基準年[2023] 32.4億美元
預測年份 [2024] 44.1億美元
預測年份 [2030] 282.6億美元
複合年成長率（%） 36.22%

市場動態：揭示快速發展的機器學習營運市場的關鍵市場洞察

機器學習營運市場正因供需的動態交互作用而轉變。了解這些不斷變化的市場動態可以幫助企業做出明智的投資決策、策略決策並抓住新的商機。全面了解這些趨勢可以幫助企業降低政治、地理、技術、社會和經濟領域的風險，並了解消費行為及其對製造成本的影響，並更清楚地了解對採購趨勢的影響。

  • 市場促進因素
    • 擴大機器學習在製造業的應用
    • 政府努力實現最終用戶部門的數位化和自動化，以提高生產力
    • 更加關注標準化機器學習流程以實現更好的管理
  • 市場限制因素
    • 由於差異而導致的與資料管理相關的問題
  • 市場機會
    • 不斷改進機器學習操作並開發新的解決方案
    • 對智慧工廠和智慧製造技術的新投資
  • 市場挑戰
    • 缺乏熟練且訓練有素的專業人員

波特的五力：駕馭機器學習營運市場的策略工具

波特的五力框架是理解市場競爭格局的重要工具。波特的五力框架為評估公司的競爭地位和探索策略機會提供了清晰的方法。該框架可幫助公司評估市場動態並確定新業務的盈利。這些見解使公司能夠利用自己的優勢，解決弱點並避免潛在的挑戰，從而確保更強大的市場地位。

PESTLE分析：了解機器學習營運市場的外部影響

外部宏觀環境因素在塑造機器學習營運市場的績效動態方面發揮著至關重要的作用。對政治、經濟、社會、技術、法律和環境因素的分析提供了應對這些影響所需的資訊。透過調查 PESTLE 因素，公司可以更了解潛在的風險和機會。這種分析可以幫助企業預測法規、消費者偏好和經濟趨勢的變化，並為他們做出積極主動的決策做好準備。

市場佔有率分析 了解機器學習營運市場的競爭狀況

機器學習營運市場的詳細市場佔有率分析提供了對供應商績效的全面評估。公司可以透過比較收益、客戶群和成長率等關鍵指標來揭示其競爭地位。該分析揭示了市場集中、分散和整合的趨勢，為供應商提供了製定策略決策所需的洞察力，以應對日益激烈的競爭。

FPNV定位矩陣機器學習營運市場廠商績效評估

FPNV 定位矩陣是評估機器學習營運市場供應商的重要工具。此矩陣允許業務組織根據商務策略和產品滿意度評估供應商，從而做出與其目標相符的明智決策。這四個象限使您能夠清晰、準確地分類供應商，以確定最能滿足您的策略目標的合作夥伴和解決方案。

策略分析和建議繪製機器學習營運市場的成功之路

機器學習營運市場的策略分析對於旨在加強其在全球市場的影響力的公司至關重要。透過審查關鍵資源、能力和績效指標，公司可以識別成長機會並努力改進。這種方法使您能夠克服競爭環境中的挑戰，利用新的商機，並取得長期成功。

本報告對市場進行了全面分析，涵蓋關鍵重點領域：

1. 市場滲透率：對當前市場環境的詳細審查、主要企業的廣泛資料、對其在市場中的影響力和整體影響力的評估。

2. 市場開拓：辨識新興市場的成長機會，評估現有領域的擴張潛力，並提供未來成長的策略藍圖。

3. 市場多元化：分析近期產品發布、開拓地區、關鍵產業進展、塑造市場的策略投資。

4. 競爭評估與情報：徹底分析競爭格局，檢驗市場佔有率、業務策略、產品系列、認證、監理核准、專利趨勢、主要企業的技術進步等。

5. 產品開發與創新：重點在於有望推動未來市場成長的最尖端科技、研發活動和產品創新。

我們也回答重要問題，幫助相關人員做出明智的決策：

1.目前的市場規模和未來的成長預測是多少？

2. 哪些產品、區隔市場和地區提供最佳投資機會？

3.塑造市場的主要技術趨勢和監管影響是什麼？

4.主要廠商的市場佔有率和競爭地位如何？

5. 推動供應商市場進入和退出策略的收益來源和策略機會是什麼？

目錄

第1章 前言

第2章調查方法

第3章執行摘要

第4章市場概況

第5章市場洞察

  • 市場動態
    • 促進因素
      • 擴大機器學習在製造業的應用
      • 政府推動最終用戶部門數位化和自動化以提高生產力的舉措
      • 更加重視標準化機器學習流程以實現更好的管理
    • 抑制因素
      • 由於差異而導致的與資料管理相關的問題
    • 機會
      • 不斷改進機器學習操作並開發新的解決方案
      • 對智慧工廠和智慧製造技術的新投資
    • 任務
      • 熟練且訓練有素的專業人員數量有限
  • 市場區隔分析
  • 波特五力分析
  • PESTEL分析
    • 政治的
    • 經濟
    • 社群
    • 技術的
    • 合法地
    • 環境

第 6 章 機器學習營運市場：依組成部分

  • 服務
  • 軟體

第 7 章 機器學習營運市場：按部署

  • 雲
  • 本地

第 8 章 機器學習營運市場：依組織規模

  • 主要企業
  • 小型企業

第 9 章 機器學習營運市場：依最終使用者分類

  • 航太和國防
  • 汽車/交通
  • 銀行、金融服務和保險
  • 建築、建築、房地產
  • 消費品/零售
  • 教育
  • 能源/公共產業
  • 政府和公共部門
  • 醫療保健和生命科學
  • 資訊科技和通訊
  • 製造業
  • 媒體與娛樂
  • 旅遊/酒店業

第10章美洲機器學習營運市場

  • 阿根廷
  • 巴西
  • 加拿大
  • 墨西哥
  • 美國

第11章 亞太地區機器學習營運市場

  • 澳洲
  • 中國
  • 印度
  • 印尼
  • 日本
  • 馬來西亞
  • 菲律賓
  • 新加坡
  • 韓國
  • 台灣
  • 泰國
  • 越南

第12章 歐洲、中東、非洲機器學習營運市場

  • 丹麥
  • 埃及
  • 芬蘭
  • 法國
  • 德國
  • 以色列
  • 義大利
  • 荷蘭
  • 奈及利亞
  • 挪威
  • 波蘭
  • 卡達
  • 俄羅斯
  • 沙烏地阿拉伯
  • 南非
  • 西班牙
  • 瑞典
  • 瑞士
  • 土耳其
  • 阿拉伯聯合大公國
  • 英國

第13章競爭格局

  • 2023 年市場佔有率分析
  • FPNV 定位矩陣，2023
  • 競爭情境分析
  • 戰略分析和建議

公司名單

  • Addepto Sp. z oo
  • Alibaba Cloud International
  • Allegro Artificial Intelligence Ltd.
  • Amazon Web Services, Inc.
  • Anyscale, Inc.
  • BigML Inc.
  • Canonical Ltd.
  • Dataiku
  • DataRobot, Inc.
  • Domino Data Lab, Inc.
  • Gathr Data Inc.
  • Google LLC by Alphabet Inc.
  • Grid Dynamics Holdings, Inc.
  • H2O.ai, Inc.
  • Hewlett Packard Enterprise Company
  • Iguazio Ltd. by McKinsey & Company
  • International Business Machines Corporation
  • Microsoft Corporation
  • Neal Analytics
  • Neptune Labs, Inc.
  • Neuro Inc.
  • Oracle Corporation
  • Runai Labs Ltd.
  • SAP SE
  • SAS Institute Inc.
  • Tredence Analytics Solutions Pvt. Ltd.
  • understandAI GmbH
  • Valohai
  • Virtusa Corporation
  • Weights and Biases, Inc.
Product Code: MRR-961BA04A2E4E

The Machine Learning Operations Market was valued at USD 3.24 billion in 2023, expected to reach USD 4.41 billion in 2024, and is projected to grow at a CAGR of 36.22%, to USD 28.26 billion by 2030.

Machine Learning Operations (MLOps) is a rapidly emerging discipline within data science that blends the principles of DevOps with machine learning to streamline the machine learning lifecycle. Its necessity stems from the growing complexities of deploying, monitoring, and maintaining machine learning models in production. With the rising implementation of AI across industries like healthcare, finance, and retail, MLOps ensures operational efficiency, reproducibility, and scalability of ML models. MLOps platforms and tools optimize workflows and reduce bottlenecks by automating processes such as data ingestion, model training, validation, and deployment, leading to faster model updates and better performance. The market is primarily fueled by increasing AI adoption in businesses, the necessity for improving model accuracy, and greater demand for scalability aligning with substantial growth in big data and cloud computing. It's projected to gain notably as industries seek to enhance decision-making and predictive capabilities through advanced AI technologies. However, challenges such as integration complexity, high initial costs, and the lack of skilled personnel can impede market growth. Security concerns and compliance issues related to data privacy also linger, presenting barriers to full-scale adoption. Opportunities lie in sectors like automated ML, real-time model monitoring, and the development of frameworks that facilitate seamless integration with existing IT environments. Firms are advised to invest in developing hybrid cloud platforms and enhancing collaboration between data scientists and IT operations to capitalize on MLOps benefits. Innovators should focus on improving open-source solutions and developing robust governance frameworks to drive broader adoption across different industries. The market is competitive yet promises modernization of AI operations, as businesses prioritize agility and efficiency, transforming how advanced analytics deliver insights and foster data-driven decision-making in today's dynamic market landscape.

KEY MARKET STATISTICS
Base Year [2023] USD 3.24 billion
Estimated Year [2024] USD 4.41 billion
Forecast Year [2030] USD 28.26 billion
CAGR (%) 36.22%

Market Dynamics: Unveiling Key Market Insights in the Rapidly Evolving Machine Learning Operations Market

The Machine Learning Operations Market is undergoing transformative changes driven by a dynamic interplay of supply and demand factors. Understanding these evolving market dynamics prepares business organizations to make informed investment decisions, refine strategic decisions, and seize new opportunities. By gaining a comprehensive view of these trends, business organizations can mitigate various risks across political, geographic, technical, social, and economic domains while also gaining a clearer understanding of consumer behavior and its impact on manufacturing costs and purchasing trends.

  • Market Drivers
    • Increasing utilization of machine learning in the manufacturing sector
    • Government initiatives to digitalize and automate end-user sectors to boost productivity
    • Growing focus on standardization of machine learning processes for better management
  • Market Restraints
    • Issues associated with data management due to discrepancies
  • Market Opportunities
    • Continuous improvements in machine learning operations and development of new solutions
    • New investments in smart factory and smart manufacturing technologies
  • Market Challenges
    • Limited availability of skilled and trained professionals

Porter's Five Forces: A Strategic Tool for Navigating the Machine Learning Operations Market

Porter's five forces framework is a critical tool for understanding the competitive landscape of the Machine Learning Operations Market. It offers business organizations with a clear methodology for evaluating their competitive positioning and exploring strategic opportunities. This framework helps businesses assess the power dynamics within the market and determine the profitability of new ventures. With these insights, business organizations can leverage their strengths, address weaknesses, and avoid potential challenges, ensuring a more resilient market positioning.

PESTLE Analysis: Navigating External Influences in the Machine Learning Operations Market

External macro-environmental factors play a pivotal role in shaping the performance dynamics of the Machine Learning Operations Market. Political, Economic, Social, Technological, Legal, and Environmental factors analysis provides the necessary information to navigate these influences. By examining PESTLE factors, businesses can better understand potential risks and opportunities. This analysis enables business organizations to anticipate changes in regulations, consumer preferences, and economic trends, ensuring they are prepared to make proactive, forward-thinking decisions.

Market Share Analysis: Understanding the Competitive Landscape in the Machine Learning Operations Market

A detailed market share analysis in the Machine Learning Operations Market provides a comprehensive assessment of vendors' performance. Companies can identify their competitive positioning by comparing key metrics, including revenue, customer base, and growth rates. This analysis highlights market concentration, fragmentation, and trends in consolidation, offering vendors the insights required to make strategic decisions that enhance their position in an increasingly competitive landscape.

FPNV Positioning Matrix: Evaluating Vendors' Performance in the Machine Learning Operations Market

The Forefront, Pathfinder, Niche, Vital (FPNV) Positioning Matrix is a critical tool for evaluating vendors within the Machine Learning Operations Market. This matrix enables business organizations to make well-informed decisions that align with their goals by assessing vendors based on their business strategy and product satisfaction. The four quadrants provide a clear and precise segmentation of vendors, helping users identify the right partners and solutions that best fit their strategic objectives.

Strategy Analysis & Recommendation: Charting a Path to Success in the Machine Learning Operations Market

A strategic analysis of the Machine Learning Operations Market is essential for businesses looking to strengthen their global market presence. By reviewing key resources, capabilities, and performance indicators, business organizations can identify growth opportunities and work toward improvement. This approach helps businesses navigate challenges in the competitive landscape and ensures they are well-positioned to capitalize on newer opportunities and drive long-term success.

Key Company Profiles

The report delves into recent significant developments in the Machine Learning Operations Market, highlighting leading vendors and their innovative profiles. These include Addepto Sp. z o. o., Alibaba Cloud International, Allegro Artificial Intelligence Ltd., Amazon Web Services, Inc., Anyscale, Inc., BigML Inc., Canonical Ltd., Dataiku, DataRobot, Inc., Domino Data Lab, Inc., Gathr Data Inc., Google LLC by Alphabet Inc., Grid Dynamics Holdings, Inc., H2O.ai, Inc., Hewlett Packard Enterprise Company, Iguazio Ltd. by McKinsey & Company, International Business Machines Corporation, Microsoft Corporation, Neal Analytics, Neptune Labs, Inc., Neuro Inc., Oracle Corporation, Runai Labs Ltd., SAP SE, SAS Institute Inc., Tredence Analytics Solutions Pvt. Ltd., understandAI GmbH, Valohai, Virtusa Corporation, and Weights and Biases, Inc..

Market Segmentation & Coverage

This research report categorizes the Machine Learning Operations Market to forecast the revenues and analyze trends in each of the following sub-markets:

  • Based on Component, market is studied across Services and Software.
  • Based on Deployment, market is studied across Cloud and On-Premise.
  • Based on Organization Size, market is studied across Large Enterprises and SMEs.
  • Based on End-User, market is studied across Aerospace & Defense, Automotive & Transportation, Banking, Financial Services & Insurance, Building, Construction & Real Estate, Consumer Goods & Retail, Education, Energy & Utilities, Government & Public Sector, Healthcare & Life Sciences, Information Technology & Telecommunication, Manufacturing, Media & Entertainment, and Travel & Hospitality.
  • Based on Region, market is studied across Americas, Asia-Pacific, and Europe, Middle East & Africa. The Americas is further studied across Argentina, Brazil, Canada, Mexico, and United States. The United States is further studied across California, Florida, Illinois, New York, Ohio, Pennsylvania, and Texas. The Asia-Pacific is further studied across Australia, China, India, Indonesia, Japan, Malaysia, Philippines, Singapore, South Korea, Taiwan, Thailand, and Vietnam. The Europe, Middle East & Africa is further studied across Denmark, Egypt, Finland, France, Germany, Israel, Italy, Netherlands, Nigeria, Norway, Poland, Qatar, Russia, Saudi Arabia, South Africa, Spain, Sweden, Switzerland, Turkey, United Arab Emirates, and United Kingdom.

The report offers a comprehensive analysis of the market, covering key focus areas:

1. Market Penetration: A detailed review of the current market environment, including extensive data from top industry players, evaluating their market reach and overall influence.

2. Market Development: Identifies growth opportunities in emerging markets and assesses expansion potential in established sectors, providing a strategic roadmap for future growth.

3. Market Diversification: Analyzes recent product launches, untapped geographic regions, major industry advancements, and strategic investments reshaping the market.

4. Competitive Assessment & Intelligence: Provides a thorough analysis of the competitive landscape, examining market share, business strategies, product portfolios, certifications, regulatory approvals, patent trends, and technological advancements of key players.

5. Product Development & Innovation: Highlights cutting-edge technologies, R&D activities, and product innovations expected to drive future market growth.

The report also answers critical questions to aid stakeholders in making informed decisions:

1. What is the current market size, and what is the forecasted growth?

2. Which products, segments, and regions offer the best investment opportunities?

3. What are the key technology trends and regulatory influences shaping the market?

4. How do leading vendors rank in terms of market share and competitive positioning?

5. What revenue sources and strategic opportunities drive vendors' market entry or exit strategies?

Table of Contents

1. Preface

  • 1.1. Objectives of the Study
  • 1.2. Market Segmentation & Coverage
  • 1.3. Years Considered for the Study
  • 1.4. Currency & Pricing
  • 1.5. Language
  • 1.6. Stakeholders

2. Research Methodology

  • 2.1. Define: Research Objective
  • 2.2. Determine: Research Design
  • 2.3. Prepare: Research Instrument
  • 2.4. Collect: Data Source
  • 2.5. Analyze: Data Interpretation
  • 2.6. Formulate: Data Verification
  • 2.7. Publish: Research Report
  • 2.8. Repeat: Report Update

3. Executive Summary

4. Market Overview

5. Market Insights

  • 5.1. Market Dynamics
    • 5.1.1. Drivers
      • 5.1.1.1. Increasing utilization of machine learning in the manufacturing sector
      • 5.1.1.2. Government initiatives to digitalize and automate end-user sectors to boost productivity
      • 5.1.1.3. Growing focus on standardization of machine learning processes for better management
    • 5.1.2. Restraints
      • 5.1.2.1. Issues associated with data management due to discrepancies
    • 5.1.3. Opportunities
      • 5.1.3.1. Continuous improvements in machine learning operations and development of new solutions
      • 5.1.3.2. New investments in smart factory and smart manufacturing technologies
    • 5.1.4. Challenges
      • 5.1.4.1. Limited availability of skilled and trained professionals
  • 5.2. Market Segmentation Analysis
  • 5.3. Porter's Five Forces Analysis
    • 5.3.1. Threat of New Entrants
    • 5.3.2. Threat of Substitutes
    • 5.3.3. Bargaining Power of Customers
    • 5.3.4. Bargaining Power of Suppliers
    • 5.3.5. Industry Rivalry
  • 5.4. PESTLE Analysis
    • 5.4.1. Political
    • 5.4.2. Economic
    • 5.4.3. Social
    • 5.4.4. Technological
    • 5.4.5. Legal
    • 5.4.6. Environmental

6. Machine Learning Operations Market, by Component

  • 6.1. Introduction
  • 6.2. Services
  • 6.3. Software

7. Machine Learning Operations Market, by Deployment

  • 7.1. Introduction
  • 7.2. Cloud
  • 7.3. On-Premise

8. Machine Learning Operations Market, by Organization Size

  • 8.1. Introduction
  • 8.2. Large Enterprises
  • 8.3. SMEs

9. Machine Learning Operations Market, by End-User

  • 9.1. Introduction
  • 9.2. Aerospace & Defense
  • 9.3. Automotive & Transportation
  • 9.4. Banking, Financial Services & Insurance
  • 9.5. Building, Construction & Real Estate
  • 9.6. Consumer Goods & Retail
  • 9.7. Education
  • 9.8. Energy & Utilities
  • 9.9. Government & Public Sector
  • 9.10. Healthcare & Life Sciences
  • 9.11. Information Technology & Telecommunication
  • 9.12. Manufacturing
  • 9.13. Media & Entertainment
  • 9.14. Travel & Hospitality

10. Americas Machine Learning Operations Market

  • 10.1. Introduction
  • 10.2. Argentina
  • 10.3. Brazil
  • 10.4. Canada
  • 10.5. Mexico
  • 10.6. United States

11. Asia-Pacific Machine Learning Operations Market

  • 11.1. Introduction
  • 11.2. Australia
  • 11.3. China
  • 11.4. India
  • 11.5. Indonesia
  • 11.6. Japan
  • 11.7. Malaysia
  • 11.8. Philippines
  • 11.9. Singapore
  • 11.10. South Korea
  • 11.11. Taiwan
  • 11.12. Thailand
  • 11.13. Vietnam

12. Europe, Middle East & Africa Machine Learning Operations Market

  • 12.1. Introduction
  • 12.2. Denmark
  • 12.3. Egypt
  • 12.4. Finland
  • 12.5. France
  • 12.6. Germany
  • 12.7. Israel
  • 12.8. Italy
  • 12.9. Netherlands
  • 12.10. Nigeria
  • 12.11. Norway
  • 12.12. Poland
  • 12.13. Qatar
  • 12.14. Russia
  • 12.15. Saudi Arabia
  • 12.16. South Africa
  • 12.17. Spain
  • 12.18. Sweden
  • 12.19. Switzerland
  • 12.20. Turkey
  • 12.21. United Arab Emirates
  • 12.22. United Kingdom

13. Competitive Landscape

  • 13.1. Market Share Analysis, 2023
  • 13.2. FPNV Positioning Matrix, 2023
  • 13.3. Competitive Scenario Analysis
  • 13.4. Strategy Analysis & Recommendation

Companies Mentioned

  • 1. Addepto Sp. z o. o.
  • 2. Alibaba Cloud International
  • 3. Allegro Artificial Intelligence Ltd.
  • 4. Amazon Web Services, Inc.
  • 5. Anyscale, Inc.
  • 6. BigML Inc.
  • 7. Canonical Ltd.
  • 8. Dataiku
  • 9. DataRobot, Inc.
  • 10. Domino Data Lab, Inc.
  • 11. Gathr Data Inc.
  • 12. Google LLC by Alphabet Inc.
  • 13. Grid Dynamics Holdings, Inc.
  • 14. H2O.ai, Inc.
  • 15. Hewlett Packard Enterprise Company
  • 16. Iguazio Ltd. by McKinsey & Company
  • 17. International Business Machines Corporation
  • 18. Microsoft Corporation
  • 19. Neal Analytics
  • 20. Neptune Labs, Inc.
  • 21. Neuro Inc.
  • 22. Oracle Corporation
  • 23. Runai Labs Ltd.
  • 24. SAP SE
  • 25. SAS Institute Inc.
  • 26. Tredence Analytics Solutions Pvt. Ltd.
  • 27. understandAI GmbH
  • 28. Valohai
  • 29. Virtusa Corporation
  • 30. Weights and Biases, Inc.

LIST OF FIGURES

  • FIGURE 1. MACHINE LEARNING OPERATIONS MARKET RESEARCH PROCESS
  • FIGURE 2. MACHINE LEARNING OPERATIONS MARKET SIZE, 2023 VS 2030
  • FIGURE 3. GLOBAL MACHINE LEARNING OPERATIONS MARKET SIZE, 2018-2030 (USD MILLION)
  • FIGURE 4. GLOBAL MACHINE LEARNING OPERATIONS MARKET SIZE, BY REGION, 2023 VS 2024 VS 2030 (USD MILLION)
  • FIGURE 5. GLOBAL MACHINE LEARNING OPERATIONS MARKET SIZE, BY COUNTRY, 2023 VS 2024 VS 2030 (USD MILLION)
  • FIGURE 6. GLOBAL MACHINE LEARNING OPERATIONS MARKET SIZE, BY COMPONENT, 2023 VS 2030 (%)
  • FIGURE 7. GLOBAL MACHINE LEARNING OPERATIONS MARKET SIZE, BY COMPONENT, 2023 VS 2024 VS 2030 (USD MILLION)
  • FIGURE 8. GLOBAL MACHINE LEARNING OPERATIONS MARKET SIZE, BY DEPLOYMENT, 2023 VS 2030 (%)
  • FIGURE 9. GLOBAL MACHINE LEARNING OPERATIONS MARKET SIZE, BY DEPLOYMENT, 2023 VS 2024 VS 2030 (USD MILLION)
  • FIGURE 10. GLOBAL MACHINE LEARNING OPERATIONS MARKET SIZE, BY ORGANIZATION SIZE, 2023 VS 2030 (%)
  • FIGURE 11. GLOBAL MACHINE LEARNING OPERATIONS MARKET SIZE, BY ORGANIZATION SIZE, 2023 VS 2024 VS 2030 (USD MILLION)
  • FIGURE 12. GLOBAL MACHINE LEARNING OPERATIONS MARKET SIZE, BY END-USER, 2023 VS 2030 (%)
  • FIGURE 13. GLOBAL MACHINE LEARNING OPERATIONS MARKET SIZE, BY END-USER, 2023 VS 2024 VS 2030 (USD MILLION)
  • FIGURE 14. AMERICAS MACHINE LEARNING OPERATIONS MARKET SIZE, BY COUNTRY, 2023 VS 2030 (%)
  • FIGURE 15. AMERICAS MACHINE LEARNING OPERATIONS MARKET SIZE, BY COUNTRY, 2023 VS 2024 VS 2030 (USD MILLION)
  • FIGURE 16. UNITED STATES MACHINE LEARNING OPERATIONS MARKET SIZE, BY STATE, 2023 VS 2030 (%)
  • FIGURE 17. UNITED STATES MACHINE LEARNING OPERATIONS MARKET SIZE, BY STATE, 2023 VS 2024 VS 2030 (USD MILLION)
  • FIGURE 18. ASIA-PACIFIC MACHINE LEARNING OPERATIONS MARKET SIZE, BY COUNTRY, 2023 VS 2030 (%)
  • FIGURE 19. ASIA-PACIFIC MACHINE LEARNING OPERATIONS MARKET SIZE, BY COUNTRY, 2023 VS 2024 VS 2030 (USD MILLION)
  • FIGURE 20. EUROPE, MIDDLE EAST & AFRICA MACHINE LEARNING OPERATIONS MARKET SIZE, BY COUNTRY, 2023 VS 2030 (%)
  • FIGURE 21. EUROPE, MIDDLE EAST & AFRICA MACHINE LEARNING OPERATIONS MARKET SIZE, BY COUNTRY, 2023 VS 2024 VS 2030 (USD MILLION)
  • FIGURE 22. MACHINE LEARNING OPERATIONS MARKET SHARE, BY KEY PLAYER, 2023
  • FIGURE 23. MACHINE LEARNING OPERATIONS MARKET, FPNV POSITIONING MATRIX, 2023

LIST OF TABLES

  • TABLE 1. MACHINE LEARNING OPERATIONS MARKET SEGMENTATION & COVERAGE
  • TABLE 2. UNITED STATES DOLLAR EXCHANGE RATE, 2018-2023
  • TABLE 3. GLOBAL MACHINE LEARNING OPERATIONS MARKET SIZE, 2018-2030 (USD MILLION)
  • TABLE 4. GLOBAL MACHINE LEARNING OPERATIONS MARKET SIZE, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 5. GLOBAL MACHINE LEARNING OPERATIONS MARKET SIZE, BY COUNTRY, 2018-2030 (USD MILLION)
  • TABLE 6. MACHINE LEARNING OPERATIONS MARKET DYNAMICS
  • TABLE 7. GLOBAL MACHINE LEARNING OPERATIONS MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 8. GLOBAL MACHINE LEARNING OPERATIONS MARKET SIZE, BY SERVICES, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 9. GLOBAL MACHINE LEARNING OPERATIONS MARKET SIZE, BY SOFTWARE, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 10. GLOBAL MACHINE LEARNING OPERATIONS MARKET SIZE, BY DEPLOYMENT, 2018-2030 (USD MILLION)
  • TABLE 11. GLOBAL MACHINE LEARNING OPERATIONS MARKET SIZE, BY CLOUD, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 12. GLOBAL MACHINE LEARNING OPERATIONS MARKET SIZE, BY ON-PREMISE, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 13. GLOBAL MACHINE LEARNING OPERATIONS MARKET SIZE, BY ORGANIZATION SIZE, 2018-2030 (USD MILLION)
  • TABLE 14. GLOBAL MACHINE LEARNING OPERATIONS MARKET SIZE, BY LARGE ENTERPRISES, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 15. GLOBAL MACHINE LEARNING OPERATIONS MARKET SIZE, BY SMES, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 16. GLOBAL MACHINE LEARNING OPERATIONS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 17. GLOBAL MACHINE LEARNING OPERATIONS MARKET SIZE, BY AEROSPACE & DEFENSE, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 18. GLOBAL MACHINE LEARNING OPERATIONS MARKET SIZE, BY AUTOMOTIVE & TRANSPORTATION, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 19. GLOBAL MACHINE LEARNING OPERATIONS MARKET SIZE, BY BANKING, FINANCIAL SERVICES & INSURANCE, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 20. GLOBAL MACHINE LEARNING OPERATIONS MARKET SIZE, BY BUILDING, CONSTRUCTION & REAL ESTATE, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 21. GLOBAL MACHINE LEARNING OPERATIONS MARKET SIZE, BY CONSUMER GOODS & RETAIL, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 22. GLOBAL MACHINE LEARNING OPERATIONS MARKET SIZE, BY EDUCATION, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 23. GLOBAL MACHINE LEARNING OPERATIONS MARKET SIZE, BY ENERGY & UTILITIES, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 24. GLOBAL MACHINE LEARNING OPERATIONS MARKET SIZE, BY GOVERNMENT & PUBLIC SECTOR, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 25. GLOBAL MACHINE LEARNING OPERATIONS MARKET SIZE, BY HEALTHCARE & LIFE SCIENCES, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 26. GLOBAL MACHINE LEARNING OPERATIONS MARKET SIZE, BY INFORMATION TECHNOLOGY & TELECOMMUNICATION, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 27. GLOBAL MACHINE LEARNING OPERATIONS MARKET SIZE, BY MANUFACTURING, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 28. GLOBAL MACHINE LEARNING OPERATIONS MARKET SIZE, BY MEDIA & ENTERTAINMENT, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 29. GLOBAL MACHINE LEARNING OPERATIONS MARKET SIZE, BY TRAVEL & HOSPITALITY, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 30. AMERICAS MACHINE LEARNING OPERATIONS MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 31. AMERICAS MACHINE LEARNING OPERATIONS MARKET SIZE, BY DEPLOYMENT, 2018-2030 (USD MILLION)
  • TABLE 32. AMERICAS MACHINE LEARNING OPERATIONS MARKET SIZE, BY ORGANIZATION SIZE, 2018-2030 (USD MILLION)
  • TABLE 33. AMERICAS MACHINE LEARNING OPERATIONS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 34. AMERICAS MACHINE LEARNING OPERATIONS MARKET SIZE, BY COUNTRY, 2018-2030 (USD MILLION)
  • TABLE 35. ARGENTINA MACHINE LEARNING OPERATIONS MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 36. ARGENTINA MACHINE LEARNING OPERATIONS MARKET SIZE, BY DEPLOYMENT, 2018-2030 (USD MILLION)
  • TABLE 37. ARGENTINA MACHINE LEARNING OPERATIONS MARKET SIZE, BY ORGANIZATION SIZE, 2018-2030 (USD MILLION)
  • TABLE 38. ARGENTINA MACHINE LEARNING OPERATIONS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 39. BRAZIL MACHINE LEARNING OPERATIONS MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 40. BRAZIL MACHINE LEARNING OPERATIONS MARKET SIZE, BY DEPLOYMENT, 2018-2030 (USD MILLION)
  • TABLE 41. BRAZIL MACHINE LEARNING OPERATIONS MARKET SIZE, BY ORGANIZATION SIZE, 2018-2030 (USD MILLION)
  • TABLE 42. BRAZIL MACHINE LEARNING OPERATIONS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 43. CANADA MACHINE LEARNING OPERATIONS MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 44. CANADA MACHINE LEARNING OPERATIONS MARKET SIZE, BY DEPLOYMENT, 2018-2030 (USD MILLION)
  • TABLE 45. CANADA MACHINE LEARNING OPERATIONS MARKET SIZE, BY ORGANIZATION SIZE, 2018-2030 (USD MILLION)
  • TABLE 46. CANADA MACHINE LEARNING OPERATIONS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 47. MEXICO MACHINE LEARNING OPERATIONS MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 48. MEXICO MACHINE LEARNING OPERATIONS MARKET SIZE, BY DEPLOYMENT, 2018-2030 (USD MILLION)
  • TABLE 49. MEXICO MACHINE LEARNING OPERATIONS MARKET SIZE, BY ORGANIZATION SIZE, 2018-2030 (USD MILLION)
  • TABLE 50. MEXICO MACHINE LEARNING OPERATIONS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 51. UNITED STATES MACHINE LEARNING OPERATIONS MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 52. UNITED STATES MACHINE LEARNING OPERATIONS MARKET SIZE, BY DEPLOYMENT, 2018-2030 (USD MILLION)
  • TABLE 53. UNITED STATES MACHINE LEARNING OPERATIONS MARKET SIZE, BY ORGANIZATION SIZE, 2018-2030 (USD MILLION)
  • TABLE 54. UNITED STATES MACHINE LEARNING OPERATIONS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 55. UNITED STATES MACHINE LEARNING OPERATIONS MARKET SIZE, BY STATE, 2018-2030 (USD MILLION)
  • TABLE 56. ASIA-PACIFIC MACHINE LEARNING OPERATIONS MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 57. ASIA-PACIFIC MACHINE LEARNING OPERATIONS MARKET SIZE, BY DEPLOYMENT, 2018-2030 (USD MILLION)
  • TABLE 58. ASIA-PACIFIC MACHINE LEARNING OPERATIONS MARKET SIZE, BY ORGANIZATION SIZE, 2018-2030 (USD MILLION)
  • TABLE 59. ASIA-PACIFIC MACHINE LEARNING OPERATIONS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 60. ASIA-PACIFIC MACHINE LEARNING OPERATIONS MARKET SIZE, BY COUNTRY, 2018-2030 (USD MILLION)
  • TABLE 61. AUSTRALIA MACHINE LEARNING OPERATIONS MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 62. AUSTRALIA MACHINE LEARNING OPERATIONS MARKET SIZE, BY DEPLOYMENT, 2018-2030 (USD MILLION)
  • TABLE 63. AUSTRALIA MACHINE LEARNING OPERATIONS MARKET SIZE, BY ORGANIZATION SIZE, 2018-2030 (USD MILLION)
  • TABLE 64. AUSTRALIA MACHINE LEARNING OPERATIONS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 65. CHINA MACHINE LEARNING OPERATIONS MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 66. CHINA MACHINE LEARNING OPERATIONS MARKET SIZE, BY DEPLOYMENT, 2018-2030 (USD MILLION)
  • TABLE 67. CHINA MACHINE LEARNING OPERATIONS MARKET SIZE, BY ORGANIZATION SIZE, 2018-2030 (USD MILLION)
  • TABLE 68. CHINA MACHINE LEARNING OPERATIONS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 69. INDIA MACHINE LEARNING OPERATIONS MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 70. INDIA MACHINE LEARNING OPERATIONS MARKET SIZE, BY DEPLOYMENT, 2018-2030 (USD MILLION)
  • TABLE 71. INDIA MACHINE LEARNING OPERATIONS MARKET SIZE, BY ORGANIZATION SIZE, 2018-2030 (USD MILLION)
  • TABLE 72. INDIA MACHINE LEARNING OPERATIONS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 73. INDONESIA MACHINE LEARNING OPERATIONS MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 74. INDONESIA MACHINE LEARNING OPERATIONS MARKET SIZE, BY DEPLOYMENT, 2018-2030 (USD MILLION)
  • TABLE 75. INDONESIA MACHINE LEARNING OPERATIONS MARKET SIZE, BY ORGANIZATION SIZE, 2018-2030 (USD MILLION)
  • TABLE 76. INDONESIA MACHINE LEARNING OPERATIONS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 77. JAPAN MACHINE LEARNING OPERATIONS MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 78. JAPAN MACHINE LEARNING OPERATIONS MARKET SIZE, BY DEPLOYMENT, 2018-2030 (USD MILLION)
  • TABLE 79. JAPAN MACHINE LEARNING OPERATIONS MARKET SIZE, BY ORGANIZATION SIZE, 2018-2030 (USD MILLION)
  • TABLE 80. JAPAN MACHINE LEARNING OPERATIONS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 81. MALAYSIA MACHINE LEARNING OPERATIONS MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 82. MALAYSIA MACHINE LEARNING OPERATIONS MARKET SIZE, BY DEPLOYMENT, 2018-2030 (USD MILLION)
  • TABLE 83. MALAYSIA MACHINE LEARNING OPERATIONS MARKET SIZE, BY ORGANIZATION SIZE, 2018-2030 (USD MILLION)
  • TABLE 84. MALAYSIA MACHINE LEARNING OPERATIONS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 85. PHILIPPINES MACHINE LEARNING OPERATIONS MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 86. PHILIPPINES MACHINE LEARNING OPERATIONS MARKET SIZE, BY DEPLOYMENT, 2018-2030 (USD MILLION)
  • TABLE 87. PHILIPPINES MACHINE LEARNING OPERATIONS MARKET SIZE, BY ORGANIZATION SIZE, 2018-2030 (USD MILLION)
  • TABLE 88. PHILIPPINES MACHINE LEARNING OPERATIONS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 89. SINGAPORE MACHINE LEARNING OPERATIONS MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 90. SINGAPORE MACHINE LEARNING OPERATIONS MARKET SIZE, BY DEPLOYMENT, 2018-2030 (USD MILLION)
  • TABLE 91. SINGAPORE MACHINE LEARNING OPERATIONS MARKET SIZE, BY ORGANIZATION SIZE, 2018-2030 (USD MILLION)
  • TABLE 92. SINGAPORE MACHINE LEARNING OPERATIONS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 93. SOUTH KOREA MACHINE LEARNING OPERATIONS MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 94. SOUTH KOREA MACHINE LEARNING OPERATIONS MARKET SIZE, BY DEPLOYMENT, 2018-2030 (USD MILLION)
  • TABLE 95. SOUTH KOREA MACHINE LEARNING OPERATIONS MARKET SIZE, BY ORGANIZATION SIZE, 2018-2030 (USD MILLION)
  • TABLE 96. SOUTH KOREA MACHINE LEARNING OPERATIONS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 97. TAIWAN MACHINE LEARNING OPERATIONS MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 98. TAIWAN MACHINE LEARNING OPERATIONS MARKET SIZE, BY DEPLOYMENT, 2018-2030 (USD MILLION)
  • TABLE 99. TAIWAN MACHINE LEARNING OPERATIONS MARKET SIZE, BY ORGANIZATION SIZE, 2018-2030 (USD MILLION)
  • TABLE 100. TAIWAN MACHINE LEARNING OPERATIONS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 101. THAILAND MACHINE LEARNING OPERATIONS MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 102. THAILAND MACHINE LEARNING OPERATIONS MARKET SIZE, BY DEPLOYMENT, 2018-2030 (USD MILLION)
  • TABLE 103. THAILAND MACHINE LEARNING OPERATIONS MARKET SIZE, BY ORGANIZATION SIZE, 2018-2030 (USD MILLION)
  • TABLE 104. THAILAND MACHINE LEARNING OPERATIONS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 105. VIETNAM MACHINE LEARNING OPERATIONS MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 106. VIETNAM MACHINE LEARNING OPERATIONS MARKET SIZE, BY DEPLOYMENT, 2018-2030 (USD MILLION)
  • TABLE 107. VIETNAM MACHINE LEARNING OPERATIONS MARKET SIZE, BY ORGANIZATION SIZE, 2018-2030 (USD MILLION)
  • TABLE 108. VIETNAM MACHINE LEARNING OPERATIONS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 109. EUROPE, MIDDLE EAST & AFRICA MACHINE LEARNING OPERATIONS MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 110. EUROPE, MIDDLE EAST & AFRICA MACHINE LEARNING OPERATIONS MARKET SIZE, BY DEPLOYMENT, 2018-2030 (USD MILLION)
  • TABLE 111. EUROPE, MIDDLE EAST & AFRICA MACHINE LEARNING OPERATIONS MARKET SIZE, BY ORGANIZATION SIZE, 2018-2030 (USD MILLION)
  • TABLE 112. EUROPE, MIDDLE EAST & AFRICA MACHINE LEARNING OPERATIONS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 113. EUROPE, MIDDLE EAST & AFRICA MACHINE LEARNING OPERATIONS MARKET SIZE, BY COUNTRY, 2018-2030 (USD MILLION)
  • TABLE 114. DENMARK MACHINE LEARNING OPERATIONS MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 115. DENMARK MACHINE LEARNING OPERATIONS MARKET SIZE, BY DEPLOYMENT, 2018-2030 (USD MILLION)
  • TABLE 116. DENMARK MACHINE LEARNING OPERATIONS MARKET SIZE, BY ORGANIZATION SIZE, 2018-2030 (USD MILLION)
  • TABLE 117. DENMARK MACHINE LEARNING OPERATIONS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 118. EGYPT MACHINE LEARNING OPERATIONS MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 119. EGYPT MACHINE LEARNING OPERATIONS MARKET SIZE, BY DEPLOYMENT, 2018-2030 (USD MILLION)
  • TABLE 120. EGYPT MACHINE LEARNING OPERATIONS MARKET SIZE, BY ORGANIZATION SIZE, 2018-2030 (USD MILLION)
  • TABLE 121. EGYPT MACHINE LEARNING OPERATIONS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 122. FINLAND MACHINE LEARNING OPERATIONS MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 123. FINLAND MACHINE LEARNING OPERATIONS MARKET SIZE, BY DEPLOYMENT, 2018-2030 (USD MILLION)
  • TABLE 124. FINLAND MACHINE LEARNING OPERATIONS MARKET SIZE, BY ORGANIZATION SIZE, 2018-2030 (USD MILLION)
  • TABLE 125. FINLAND MACHINE LEARNING OPERATIONS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 126. FRANCE MACHINE LEARNING OPERATIONS MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 127. FRANCE MACHINE LEARNING OPERATIONS MARKET SIZE, BY DEPLOYMENT, 2018-2030 (USD MILLION)
  • TABLE 128. FRANCE MACHINE LEARNING OPERATIONS MARKET SIZE, BY ORGANIZATION SIZE, 2018-2030 (USD MILLION)
  • TABLE 129. FRANCE MACHINE LEARNING OPERATIONS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 130. GERMANY MACHINE LEARNING OPERATIONS MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 131. GERMANY MACHINE LEARNING OPERATIONS MARKET SIZE, BY DEPLOYMENT, 2018-2030 (USD MILLION)
  • TABLE 132. GERMANY MACHINE LEARNING OPERATIONS MARKET SIZE, BY ORGANIZATION SIZE, 2018-2030 (USD MILLION)
  • TABLE 133. GERMANY MACHINE LEARNING OPERATIONS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 134. ISRAEL MACHINE LEARNING OPERATIONS MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 135. ISRAEL MACHINE LEARNING OPERATIONS MARKET SIZE, BY DEPLOYMENT, 2018-2030 (USD MILLION)
  • TABLE 136. ISRAEL MACHINE LEARNING OPERATIONS MARKET SIZE, BY ORGANIZATION SIZE, 2018-2030 (USD MILLION)
  • TABLE 137. ISRAEL MACHINE LEARNING OPERATIONS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 138. ITALY MACHINE LEARNING OPERATIONS MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 139. ITALY MACHINE LEARNING OPERATIONS MARKET SIZE, BY DEPLOYMENT, 2018-2030 (USD MILLION)
  • TABLE 140. ITALY MACHINE LEARNING OPERATIONS MARKET SIZE, BY ORGANIZATION SIZE, 2018-2030 (USD MILLION)
  • TABLE 141. ITALY MACHINE LEARNING OPERATIONS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 142. NETHERLANDS MACHINE LEARNING OPERATIONS MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 143. NETHERLANDS MACHINE LEARNING OPERATIONS MARKET SIZE, BY DEPLOYMENT, 2018-2030 (USD MILLION)
  • TABLE 144. NETHERLANDS MACHINE LEARNING OPERATIONS MARKET SIZE, BY ORGANIZATION SIZE, 2018-2030 (USD MILLION)
  • TABLE 145. NETHERLANDS MACHINE LEARNING OPERATIONS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 146. NIGERIA MACHINE LEARNING OPERATIONS MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 147. NIGERIA MACHINE LEARNING OPERATIONS MARKET SIZE, BY DEPLOYMENT, 2018-2030 (USD MILLION)
  • TABLE 148. NIGERIA MACHINE LEARNING OPERATIONS MARKET SIZE, BY ORGANIZATION SIZE, 2018-2030 (USD MILLION)
  • TABLE 149. NIGERIA MACHINE LEARNING OPERATIONS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 150. NORWAY MACHINE LEARNING OPERATIONS MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 151. NORWAY MACHINE LEARNING OPERATIONS MARKET SIZE, BY DEPLOYMENT, 2018-2030 (USD MILLION)
  • TABLE 152. NORWAY MACHINE LEARNING OPERATIONS MARKET SIZE, BY ORGANIZATION SIZE, 2018-2030 (USD MILLION)
  • TABLE 153. NORWAY MACHINE LEARNING OPERATIONS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 154. POLAND MACHINE LEARNING OPERATIONS MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 155. POLAND MACHINE LEARNING OPERATIONS MARKET SIZE, BY DEPLOYMENT, 2018-2030 (USD MILLION)
  • TABLE 156. POLAND MACHINE LEARNING OPERATIONS MARKET SIZE, BY ORGANIZATION SIZE, 2018-2030 (USD MILLION)
  • TABLE 157. POLAND MACHINE LEARNING OPERATIONS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 158. QATAR MACHINE LEARNING OPERATIONS MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 159. QATAR MACHINE LEARNING OPERATIONS MARKET SIZE, BY DEPLOYMENT, 2018-2030 (USD MILLION)
  • TABLE 160. QATAR MACHINE LEARNING OPERATIONS MARKET SIZE, BY ORGANIZATION SIZE, 2018-2030 (USD MILLION)
  • TABLE 161. QATAR MACHINE LEARNING OPERATIONS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 162. RUSSIA MACHINE LEARNING OPERATIONS MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 163. RUSSIA MACHINE LEARNING OPERATIONS MARKET SIZE, BY DEPLOYMENT, 2018-2030 (USD MILLION)
  • TABLE 164. RUSSIA MACHINE LEARNING OPERATIONS MARKET SIZE, BY ORGANIZATION SIZE, 2018-2030 (USD MILLION)
  • TABLE 165. RUSSIA MACHINE LEARNING OPERATIONS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 166. SAUDI ARABIA MACHINE LEARNING OPERATIONS MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 167. SAUDI ARABIA MACHINE LEARNING OPERATIONS MARKET SIZE, BY DEPLOYMENT, 2018-2030 (USD MILLION)
  • TABLE 168. SAUDI ARABIA MACHINE LEARNING OPERATIONS MARKET SIZE, BY ORGANIZATION SIZE, 2018-2030 (USD MILLION)
  • TABLE 169. SAUDI ARABIA MACHINE LEARNING OPERATIONS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 170. SOUTH AFRICA MACHINE LEARNING OPERATIONS MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 171. SOUTH AFRICA MACHINE LEARNING OPERATIONS MARKET SIZE, BY DEPLOYMENT, 2018-2030 (USD MILLION)
  • TABLE 172. SOUTH AFRICA MACHINE LEARNING OPERATIONS MARKET SIZE, BY ORGANIZATION SIZE, 2018-2030 (USD MILLION)
  • TABLE 173. SOUTH AFRICA MACHINE LEARNING OPERATIONS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 174. SPAIN MACHINE LEARNING OPERATIONS MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 175. SPAIN MACHINE LEARNING OPERATIONS MARKET SIZE, BY DEPLOYMENT, 2018-2030 (USD MILLION)
  • TABLE 176. SPAIN MACHINE LEARNING OPERATIONS MARKET SIZE, BY ORGANIZATION SIZE, 2018-2030 (USD MILLION)
  • TABLE 177. SPAIN MACHINE LEARNING OPERATIONS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 178. SWEDEN MACHINE LEARNING OPERATIONS MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 179. SWEDEN MACHINE LEARNING OPERATIONS MARKET SIZE, BY DEPLOYMENT, 2018-2030 (USD MILLION)
  • TABLE 180. SWEDEN MACHINE LEARNING OPERATIONS MARKET SIZE, BY ORGANIZATION SIZE, 2018-2030 (USD MILLION)
  • TABLE 181. SWEDEN MACHINE LEARNING OPERATIONS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 182. SWITZERLAND MACHINE LEARNING OPERATIONS MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 183. SWITZERLAND MACHINE LEARNING OPERATIONS MARKET SIZE, BY DEPLOYMENT, 2018-2030 (USD MILLION)
  • TABLE 184. SWITZERLAND MACHINE LEARNING OPERATIONS MARKET SIZE, BY ORGANIZATION SIZE, 2018-2030 (USD MILLION)
  • TABLE 185. SWITZERLAND MACHINE LEARNING OPERATIONS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 186. TURKEY MACHINE LEARNING OPERATIONS MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 187. TURKEY MACHINE LEARNING OPERATIONS MARKET SIZE, BY DEPLOYMENT, 2018-2030 (USD MILLION)
  • TABLE 188. TURKEY MACHINE LEARNING OPERATIONS MARKET SIZE, BY ORGANIZATION SIZE, 2018-2030 (USD MILLION)
  • TABLE 189. TURKEY MACHINE LEARNING OPERATIONS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 190. UNITED ARAB EMIRATES MACHINE LEARNING OPERATIONS MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 191. UNITED ARAB EMIRATES MACHINE LEARNING OPERATIONS MARKET SIZE, BY DEPLOYMENT, 2018-2030 (USD MILLION)
  • TABLE 192. UNITED ARAB EMIRATES MACHINE LEARNING OPERATIONS MARKET SIZE, BY ORGANIZATION SIZE, 2018-2030 (USD MILLION)
  • TABLE 193. UNITED ARAB EMIRATES MACHINE LEARNING OPERATIONS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 194. UNITED KINGDOM MACHINE LEARNING OPERATIONS MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 195. UNITED KINGDOM MACHINE LEARNING OPERATIONS MARKET SIZE, BY DEPLOYMENT, 2018-2030 (USD MILLION)
  • TABLE 196. UNITED KINGDOM MACHINE LEARNING OPERATIONS MARKET SIZE, BY ORGANIZATION SIZE, 2018-2030 (USD MILLION)
  • TABLE 197. UNITED KINGDOM MACHINE LEARNING OPERATIONS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 198. MACHINE LEARNING OPERATIONS MARKET SHARE, BY KEY PLAYER, 2023
  • TABLE 199. MACHINE LEARNING OPERATIONS MARKET, FPNV POSITIONING MATRIX, 2023