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市场调查报告书
商品编码
1693208

2025年全球机器学习营运市场报告

Machine Learning Operations Global Market Report 2025
出版日期: | 出版商: The Business Research Company | 英文 200 Pages | 商品交期: 2-10个工作天内

价格
简介目录

预计未来几年机器学习营运的市场规模将呈指数级增长。到 2029 年，这一数字将成长至 108.4 亿美元，复合年增长率为 38.0%。预测期内的成长可归因于云端运算的兴起、产业对机器学习的日益采用、模型部署技术的发展、敏捷开发实践的采用以及机器学习模型的日益复杂化。预测期内的关键趋势包括分析整合度的提高、机器学习的民主化、边缘 AI 应用的指数级增长、自动超参数调整以及 MLOps 管道安全性的提高。

对自动驾驶汽车日益增长的需求将推动机器学习营运 (MLOps) 市场的成长。自动驾驶汽车配备了先进的传感器、摄影机、雷达、光达和人工智慧 (AI) 系统，使其能够在没有人工直接干预的情况下在道路上导航和做出决策。自动驾驶汽车中的 MLOps 涉及车辆内机器学习模型的持续整合、部署和管理。这使得汽车能够根据来自感测器的即时数据和不同的驾驶场景来调整和改善其驾驶能力。根据美国公路安全美国协会 (ISI) 2022 年 12 月发布的报告，到 2025 年，美国道路上将有 350 万辆自动驾驶汽车，到 2030 年将增加到 450 万辆。自动驾驶汽车需求的激增被认为是机器学习业务市场的主要驱动力。

机器学习营运 (MLOps) 市场的主要企业正在采用创新解决方案，例如用于 MLOps 的 GPT 监控。 MLOps 的 GPT 监控支援对 GPT 模型进行即时监控和成本跟踪，从而提高工程团队的效能和营运效率。 MLOps 的 GPT 监控利用预先训练的生成转换器来更好地追踪和管理机器学习操作，从而实现更好的模型效能和决策。例如，2023年3月，美国数位智慧公司New Relic宣布推出New Relic机器学习营运（MLOps），利用OpenAI的GPT系列API对应用程式进行即时监控。此新功能使工程团队仅使用两行程式码即可监控效能和成本，从而即时了解 GPT 的使用情况。它支援OpenAI GPT的所有版本，并帮助企业优化AI主导的应用程序，同时降低营运成本。

目录

第一章执行摘要

第二章 市场特征

第三章 市场趋势与策略

第四章 市场－宏观经济情景，包括利率、通膨、地缘政治、新冠疫情、以及復苏对市场的影响

第五章 全球成长分析与策略分析框架

  • 全球机器学习营运市场的 PESTEL 分析（政治、社会、技术、环境、法律因素、驱动因素和限制因素）
  • 最终用途产业分析
  • 全球机器学习营运市场：成长率分析
  • 全球机器学习营运市场表现：规模与成长，2019-2024
  • 全球机器学习营运市场预测：规模与成长，2024-2029 年，2034 年
  • 全球机器学习营运总目标市场（TAM）

第六章市场区隔

  • 全球机器学习营运市场（按部署类型、效能和预测），2019-2024 年、2024-2029 年、2034 年
  • 本地
  • 云
  • 其他的
  • 全球机器学习营运市场（依组织规模、绩效与预测），2019-2024 年、2024-2029 年、2034 年
  • 大型企业
  • 中小型企业
  • 全球机器学习营运市场（依产业垂直、绩效及预测），2019-2024 年、2024-2029 年、2034 年
  • BFSI（银行、金融服务、保险）
  • 製造业
  • 资讯科技/通讯
  • 零售与电子商务
  • 能源与公共
  • 卫生保健
  • 媒体与娱乐
  • 其他的
  • 全球机器学习营运市场 - 按类型、效能和预测进行的内部细分，2019-2024 年、2024-2029 年、2034 年
  • 私人资料中心
  • 本地伺服器
  • 全球机器学习营运市场：按类型、效能和预测分類的云端细分市场，2019-2024 年、2024-2029 年、2034 年
  • 公共云端服务
  • 混合云端解决方案
  • 多重云端环境
  • 全球机器学习营运市场：其他细分市场：按类型、实际和预测，2019-2024 年、2024-2029 年、2034 年
  • 边缘配置
  • 混合本地或云端解决方案

第七章 区域和国家分析

  • 全球机器学习营运市场（按地区、绩效及预测），2019-2024 年、2024-2029 年、2034 年
  • 全球机器学习营运市场（依国家/地区、绩效及预测）2019-2024、2024-2029、2034

第八章 亚太市场

第九章：中国市场

第十章 印度市场

第十一章 日本市场

第十二章 澳洲市场

第十三章 印尼市场

第十四章 韩国市场

第十五章 西欧市场

第十六章英国市场

第十七章 德国市场

第十八章 法国市场

第十九章：义大利市场

第20章：西班牙市场

第21章 东欧市场

第22章 俄罗斯市场

第23章 北美市场

第24章美国市场

第25章：加拿大市场

第26章 南美洲市场

第27章：巴西市场

第28章 中东市场

第29章：非洲市场

第30章竞争格局与公司概况

  • 机器学习营运市场：竞争格局
  • 机器学习营运市场：公司简介
    • Amazon.com Inc. Overview, Products and Services, Strategy and Financial Analysis
    • Alphabet Inc. Overview, Products and Services, Strategy and Financial Analysis
    • Microsoft Corporation Overview, Products and Services, Strategy and Financial Analysis
    • International Business Machines Corporation Overview, Products and Services, Strategy and Financial Analysis
    • Hewlett Packard Enterprise Overview, Products and Services, Strategy and Financial Analysis

第31章 其他大型创新企业

  • Statistical Analysis System（SAS）
  • Databricks Inc.
  • Cloudera Inc.
  • Alteryx Inc.
  • Comet
  • GAVS Technologies
  • DataRobot Inc.
  • Veritone
  • Dataiku
  • Parallel LLC
  • Neptune Labs
  • SparkCognition
  • Weights & Biases
  • Kensho Technologies Inc.
  • Akira.Al

第 32 章全球市场竞争基准化分析与仪表板

第33章 重大併购

第34章近期市场趋势

第 35 章 高市场潜力国家、细分市场与策略

  • 2029 年机器学习营运市场：提供新机会的国家
  • 2029 年机器学习营运市场：细分领域带来新机会
  • 2029 年机器学习营运市场：成长策略
    • 基于市场趋势的策略
    • 竞争对手的策略

第36章 附录

简介目录
Product Code: r28448

Machine Learning Operations, often referred to as MLOps, encompasses a set of practices and tools designed to automate and manage the complete lifecycle of machine learning models, starting from their development and training phases. MLOps involves a range of tasks related to deploying, managing, and monitoring machine learning models in production environments. It aims to streamline and enhance the efficiency of the operational aspects associated with the deployment and ongoing maintenance of machine learning solutions.

The primary types of deployments in Machine Learning Operations (MLOps) include on-premise, cloud, and other variations. On-premise deployment involves installing and running software or systems within an organization's physical infrastructure or data centers. This deployment method caters to enterprises of various sizes, including large enterprises and small to medium-sized enterprises. On-premise MLOps finds applications across diverse industry sectors such as banking, financial services, and insurance (BFSI), manufacturing, IT and telecom, retail, and e-commerce, energy and utility, healthcare, media and entertainment, among others.

The machine learning operations market research report is one of a series of new reports from The Business Research Company that provides machine learning operations market statistics, including machine learning operations industry global market size, regional shares, competitors with machine learning operations market share, detailed machine learning operations market segments, market trends, and opportunities, and any further data you may need to thrive in the machine learning operations industry. This machine learning operations market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future scenarios of the industry.

The machine learning operations market size has grown exponentially in recent years. It will grow from $2.16 billion in 2024 to $2.99 billion in 2025 at a compound annual growth rate (CAGR) of 38.4%. The growth in the historic period can be attributed to increasing complexity of ml models, rapid evolution of edge computing, increasing adoption of federated learning, continuous integration of devops and mlops, surge in automl adoption.

The machine learning operations market size is expected to see exponential growth in the next few years. It will grow to $10.84 billion in 2029 at a compound annual growth rate (CAGR) of 38.0%. The growth in the forecast period can be attributed to rise of cloud computing, increased adoption of machine learning in industries, development of model deployment technologies, adoption of agile development practices, increased complexity of machine learning models. Major trends in the forecast period include augmented analytics integration, democratization of machine learning, exponential growth in edge ai applications, automated hyperparameter tuning, enhanced security in mlops pipelines.

The increasing demand for self-driving cars is poised to drive the growth of the machine-learning operations (MLOps) market. Self-driving cars are equipped with advanced sensors, cameras, radar, lidar, and artificial intelligence (AI) systems that enable them to navigate and make decisions on the road without direct human intervention. MLOps in self-driving cars involves the continuous integration, deployment, and management of machine learning models within the vehicles. This allows them to adapt and improve their driving capabilities based on real-time data from sensors and diverse driving scenarios. According to a report from the Insurance Institute for Highway Safety in December 2022, an estimated 3.5 million autonomous vehicles are projected to be on American roads by 2025, with expectations for this number to increase to 4.5 million by 2030. The surging demand for self-driving cars is identified as a significant driver of the machine-learning operations market.

Major companies in the machine learning operations (MLOps) market are introducing innovative solutions such as GPT Monitoring for MLOps, which allows for real-time monitoring and cost tracking of GPT models, enhancing performance and operational efficiency for engineering teams. GPT Monitoring for MLOps leverages generative pre-trained transformers to improve the tracking and management of machine learning operations, enabling better model performance and decision-making. For example, in March 2023, New Relic, a U.S.-based digital intelligence company, launched New Relic Machine Learning Operations (MLOps) for real-time monitoring of applications using OpenAI's GPT series APIs. This new feature enables engineering teams to monitor performance and costs with just two lines of code, offering immediate insights into GPT usage. It supports all versions of OpenAI GPT, helping companies optimize AI-driven applications while reducing operational costs.

In March 2024, Bain & Company, a U.S.-based management consulting services firm, acquired PiperLab for an undisclosed amount. This acquisition aims to bolster Bain's artificial intelligence (AI) and machine learning (ML) capabilities across Europe, the Middle East, and Africa (EMEA). By integrating PiperLab's expertise and solutions, Bain plans to create an additional hub within its global Advanced Analytics Group (AAG), enabling a unified team to address complex business challenges at the intersection of business, data science, and engineering. PiperLab, a Spain-based company, specializes in providing data-driven solutions that focus on enhancing operational efficiency, increasing productivity, and reducing costs for businesses.

Major companies operating in the machine learning operations market report are Amazon.com Inc., Alphabet Inc., Microsoft Corporation, International Business Machines Corporation, Hewlett Packard Enterprise, Statistical Analysis System (SAS ), Databricks Inc., Cloudera Inc., Alteryx Inc., Comet, GAVS Technologies, DataRobot Inc., Veritone, Dataiku, Parallel LLC, Neptune Labs, SparkCognition, Weights & Biases, Kensho Technologies Inc., Akira.Al, Iguazio, Domino Data Lab, Symphony Solutions, Valohai, Blaize, Neptune.ai, H2O.ai, Paperspace, OctoML

North America was the largest region in the machine learning operations market in 2024. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the machine learning operations market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.

The countries covered in the machine learning operations market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Russia, South Korea, UK, USA, Canada, Italy, Spain

The machine learning operations market includes revenues earned by entities by providing services including model deployment services, integration services, data management services, cloud services and testing services. The market value includes the value of related goods sold by the service provider or included within the service offering. Only goods and services traded between entities or sold to end consumers are included. The machine learning operations market consists of sales of central processing units (CPUs), graphics processing units (GPUs), field-programmable gate arrays (FPGAs), and tensor processing units (TPUs). Values in this market are 'factory gate' values, that is the value of goods sold by the manufacturers or creators of the goods, whether to other entities (including downstream manufacturers, wholesalers, distributors and retailers) or directly to end customers. The value of goods in this market includes related services sold by the creators of the goods.

The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD, unless otherwise specified).

The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.

Machine Learning Operations Global Market Report 2025 from The Business Research Company provides strategists, marketers and senior management with the critical information they need to assess the market.

This report focuses on machine learning operations market which is experiencing strong growth. The report gives a guide to the trends which will be shaping the market over the next ten years and beyond.

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Where is the largest and fastest growing market for machine learning operations ? How does the market relate to the overall economy, demography and other similar markets? What forces will shape the market going forward? The machine learning operations market global report from the Business Research Company answers all these questions and many more.

The report covers market characteristics, size and growth, segmentation, regional and country breakdowns, competitive landscape, market shares, trends and strategies for this market. It traces the market's historic and forecast market growth by geography.

  • The market characteristics section of the report defines and explains the market.
  • The market size section gives the market size ($b) covering both the historic growth of the market, and forecasting its development.
  • The forecasts are made after considering the major factors currently impacting the market. These include:

The forecasts are made after considering the major factors currently impacting the market. These include the Russia-Ukraine war, rising inflation, higher interest rates, and the legacy of the COVID-19 pandemic.

  • Market segmentations break down the market into sub markets.
  • The regional and country breakdowns section gives an analysis of the market in each geography and the size of the market by geography and compares their historic and forecast growth. It covers the growth trajectory of COVID-19 for all regions, key developed countries and major emerging markets.
  • The competitive landscape chapter gives a description of the competitive nature of the market, market shares, and a description of the leading companies. Key financial deals which have shaped the market in recent years are identified.
  • The trends and strategies section analyses the shape of the market as it emerges from the crisis and suggests how companies can grow as the market recovers.

Scope

  • Markets Covered:1) By Deployment Type: On-Premise; Cloud; Other Type Of Deployment
  • 2) By Organization Size: Large Enterprises; Small And Medium-sized Enterprises
  • 3) By Industry Vertical: BFSI (Banking, Financial Services, And Insurance); Manufacturing; IT And Telecom; Retail And E-commerce; Energy And Utility; Healthcare; Media And Entertainment; Other Industry Verticals
  • Subsegments:
  • 1) By On-Premise: Private Data Centers; Local Servers
  • 2) By Cloud: Public Cloud Services; Hybrid Cloud Solutions; Multi-Cloud Environments
  • 3) By Other Type Of Deployment: Edge Deployment; Hybrid On-Premise Or Cloud Solutions
  • Companies Mentioned: Amazon.com Inc.; Alphabet Inc.; Microsoft Corporation; International Business Machines Corporation; Hewlett Packard Enterprise
  • Countries: Australia; Brazil; China; France; Germany; India; Indonesia; Japan; Russia; South Korea; UK; USA; Canada; Italy; Spain
  • Regions: Asia-Pacific; Western Europe; Eastern Europe; North America; South America; Middle East; Africa
  • Time series: Five years historic and ten years forecast.
  • Data: Ratios of market size and growth to related markets, GDP proportions, expenditure per capita,
  • Data segmentations: country and regional historic and forecast data, market share of competitors, market segments.
  • Sourcing and Referencing: Data and analysis throughout the report is sourced using end notes.
  • Delivery format: PDF, Word and Excel Data Dashboard.

Table of Contents

1. Executive Summary

2. Machine Learning Operations Market Characteristics

3. Machine Learning Operations Market Trends And Strategies

4. Machine Learning Operations Market - Macro Economic Scenario Including The Impact Of Interest Rates, Inflation, Geopolitics, Covid And Recovery On The Market

5. Global Machine Learning Operations Growth Analysis And Strategic Analysis Framework

  • 5.1. Global Machine Learning Operations PESTEL Analysis (Political, Social, Technological, Environmental and Legal Factors, Drivers and Restraints)
  • 5.2. Analysis Of End Use Industries
  • 5.3. Global Machine Learning Operations Market Growth Rate Analysis
  • 5.4. Global Machine Learning Operations Historic Market Size and Growth, 2019 - 2024, Value ($ Billion)
  • 5.5. Global Machine Learning Operations Forecast Market Size and Growth, 2024 - 2029, 2034F, Value ($ Billion)
  • 5.6. Global Machine Learning Operations Total Addressable Market (TAM)

6. Machine Learning Operations Market Segmentation

  • 6.1. Global Machine Learning Operations Market, Segmentation By Deployment Type, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • On-Premise
  • Cloud
  • Other Type Of Deployment
  • 6.2. Global Machine Learning Operations Market, Segmentation By Organization Size, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • Large Enterprises
  • Small And Medium-Sized Enterprises
  • 6.3. Global Machine Learning Operations Market, Segmentation By Industry Vertical, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • BFSI (Banking, Financial Services, And Insurance)
  • Manufacturing
  • IT And Telecom
  • Retail And E-commerce
  • Energy And Utility
  • Healthcare
  • Media And Entertainment
  • Other Industry Verticals
  • 6.4. Global Machine Learning Operations Market, Sub-Segmentation Of On-Premise, By Type, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • Private Data Centers
  • Local Servers
  • 6.5. Global Machine Learning Operations Market, Sub-Segmentation Of Cloud, By Type, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • Public Cloud Services
  • Hybrid Cloud Solutions
  • Multi-Cloud Environments
  • 6.6. Global Machine Learning Operations Market, Sub-Segmentation Of Other Type Of Deployment, By Type, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • Edge Deployment
  • Hybrid On-Premise Or Cloud Solutions

7. Machine Learning Operations Market Regional And Country Analysis

  • 7.1. Global Machine Learning Operations Market, Split By Region, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 7.2. Global Machine Learning Operations Market, Split By Country, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

8. Asia-Pacific Machine Learning Operations Market

  • 8.1. Asia-Pacific Machine Learning Operations Market Overview
  • Region Information, Market Information, Background Information, Government Initiatives, Regulations, Regulatory Bodies, Major Associations, Taxes Levied, Corporate Tax Structure, Investments, Major Companies
  • 8.2. Asia-Pacific Machine Learning Operations Market, Segmentation By Deployment Type, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 8.3. Asia-Pacific Machine Learning Operations Market, Segmentation By Organization Size, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 8.4. Asia-Pacific Machine Learning Operations Market, Segmentation By Industry Vertical, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

9. China Machine Learning Operations Market

  • 9.1. China Machine Learning Operations Market Overview
  • 9.2. China Machine Learning Operations Market, Segmentation By Deployment Type, Historic and Forecast, 2019-2024, 2024-2029F, 2034F,$ Billion
  • 9.3. China Machine Learning Operations Market, Segmentation By Organization Size, Historic and Forecast, 2019-2024, 2024-2029F, 2034F,$ Billion
  • 9.4. China Machine Learning Operations Market, Segmentation By Industry Vertical, Historic and Forecast, 2019-2024, 2024-2029F, 2034F,$ Billion

10. India Machine Learning Operations Market

  • 10.1. India Machine Learning Operations Market, Segmentation By Deployment Type, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 10.2. India Machine Learning Operations Market, Segmentation By Organization Size, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 10.3. India Machine Learning Operations Market, Segmentation By Industry Vertical, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

11. Japan Machine Learning Operations Market

  • 11.1. Japan Machine Learning Operations Market Overview
  • 11.2. Japan Machine Learning Operations Market, Segmentation By Deployment Type, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 11.3. Japan Machine Learning Operations Market, Segmentation By Organization Size, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 11.4. Japan Machine Learning Operations Market, Segmentation By Industry Vertical, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

12. Australia Machine Learning Operations Market

  • 12.1. Australia Machine Learning Operations Market, Segmentation By Deployment Type, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 12.2. Australia Machine Learning Operations Market, Segmentation By Organization Size, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 12.3. Australia Machine Learning Operations Market, Segmentation By Industry Vertical, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

13. Indonesia Machine Learning Operations Market

  • 13.1. Indonesia Machine Learning Operations Market, Segmentation By Deployment Type, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 13.2. Indonesia Machine Learning Operations Market, Segmentation By Organization Size, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 13.3. Indonesia Machine Learning Operations Market, Segmentation By Industry Vertical, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

14. South Korea Machine Learning Operations Market

  • 14.1. South Korea Machine Learning Operations Market Overview
  • 14.2. South Korea Machine Learning Operations Market, Segmentation By Deployment Type, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 14.3. South Korea Machine Learning Operations Market, Segmentation By Organization Size, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 14.4. South Korea Machine Learning Operations Market, Segmentation By Industry Vertical, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

15. Western Europe Machine Learning Operations Market

  • 15.1. Western Europe Machine Learning Operations Market Overview
  • 15.2. Western Europe Machine Learning Operations Market, Segmentation By Deployment Type, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 15.3. Western Europe Machine Learning Operations Market, Segmentation By Organization Size, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 15.4. Western Europe Machine Learning Operations Market, Segmentation By Industry Vertical, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

16. UK Machine Learning Operations Market

  • 16.1. UK Machine Learning Operations Market, Segmentation By Deployment Type, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 16.2. UK Machine Learning Operations Market, Segmentation By Organization Size, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 16.3. UK Machine Learning Operations Market, Segmentation By Industry Vertical, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

17. Germany Machine Learning Operations Market

  • 17.1. Germany Machine Learning Operations Market, Segmentation By Deployment Type, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 17.2. Germany Machine Learning Operations Market, Segmentation By Organization Size, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 17.3. Germany Machine Learning Operations Market, Segmentation By Industry Vertical, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

18. France Machine Learning Operations Market

  • 18.1. France Machine Learning Operations Market, Segmentation By Deployment Type, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 18.2. France Machine Learning Operations Market, Segmentation By Organization Size, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 18.3. France Machine Learning Operations Market, Segmentation By Industry Vertical, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

19. Italy Machine Learning Operations Market

  • 19.1. Italy Machine Learning Operations Market, Segmentation By Deployment Type, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 19.2. Italy Machine Learning Operations Market, Segmentation By Organization Size, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 19.3. Italy Machine Learning Operations Market, Segmentation By Industry Vertical, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

20. Spain Machine Learning Operations Market

  • 20.1. Spain Machine Learning Operations Market, Segmentation By Deployment Type, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 20.2. Spain Machine Learning Operations Market, Segmentation By Organization Size, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 20.3. Spain Machine Learning Operations Market, Segmentation By Industry Vertical, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

21. Eastern Europe Machine Learning Operations Market

  • 21.1. Eastern Europe Machine Learning Operations Market Overview
  • 21.2. Eastern Europe Machine Learning Operations Market, Segmentation By Deployment Type, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 21.3. Eastern Europe Machine Learning Operations Market, Segmentation By Organization Size, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 21.4. Eastern Europe Machine Learning Operations Market, Segmentation By Industry Vertical, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

22. Russia Machine Learning Operations Market

  • 22.1. Russia Machine Learning Operations Market, Segmentation By Deployment Type, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 22.2. Russia Machine Learning Operations Market, Segmentation By Organization Size, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 22.3. Russia Machine Learning Operations Market, Segmentation By Industry Vertical, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

23. North America Machine Learning Operations Market

  • 23.1. North America Machine Learning Operations Market Overview
  • 23.2. North America Machine Learning Operations Market, Segmentation By Deployment Type, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 23.3. North America Machine Learning Operations Market, Segmentation By Organization Size, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 23.4. North America Machine Learning Operations Market, Segmentation By Industry Vertical, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

24. USA Machine Learning Operations Market

  • 24.1. USA Machine Learning Operations Market Overview
  • 24.2. USA Machine Learning Operations Market, Segmentation By Deployment Type, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 24.3. USA Machine Learning Operations Market, Segmentation By Organization Size, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 24.4. USA Machine Learning Operations Market, Segmentation By Industry Vertical, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

25. Canada Machine Learning Operations Market

  • 25.1. Canada Machine Learning Operations Market Overview
  • 25.2. Canada Machine Learning Operations Market, Segmentation By Deployment Type, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 25.3. Canada Machine Learning Operations Market, Segmentation By Organization Size, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 25.4. Canada Machine Learning Operations Market, Segmentation By Industry Vertical, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

26. South America Machine Learning Operations Market

  • 26.1. South America Machine Learning Operations Market Overview
  • 26.2. South America Machine Learning Operations Market, Segmentation By Deployment Type, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 26.3. South America Machine Learning Operations Market, Segmentation By Organization Size, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 26.4. South America Machine Learning Operations Market, Segmentation By Industry Vertical, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

27. Brazil Machine Learning Operations Market

  • 27.1. Brazil Machine Learning Operations Market, Segmentation By Deployment Type, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 27.2. Brazil Machine Learning Operations Market, Segmentation By Organization Size, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 27.3. Brazil Machine Learning Operations Market, Segmentation By Industry Vertical, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

28. Middle East Machine Learning Operations Market

  • 28.1. Middle East Machine Learning Operations Market Overview
  • 28.2. Middle East Machine Learning Operations Market, Segmentation By Deployment Type, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 28.3. Middle East Machine Learning Operations Market, Segmentation By Organization Size, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 28.4. Middle East Machine Learning Operations Market, Segmentation By Industry Vertical, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

29. Africa Machine Learning Operations Market

  • 29.1. Africa Machine Learning Operations Market Overview
  • 29.2. Africa Machine Learning Operations Market, Segmentation By Deployment Type, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 29.3. Africa Machine Learning Operations Market, Segmentation By Organization Size, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 29.4. Africa Machine Learning Operations Market, Segmentation By Industry Vertical, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

30. Machine Learning Operations Market Competitive Landscape And Company Profiles

  • 30.1. Machine Learning Operations Market Competitive Landscape
  • 30.2. Machine Learning Operations Market Company Profiles
    • 30.2.1. Amazon.com Inc. Overview, Products and Services, Strategy and Financial Analysis
    • 30.2.2. Alphabet Inc. Overview, Products and Services, Strategy and Financial Analysis
    • 30.2.3. Microsoft Corporation Overview, Products and Services, Strategy and Financial Analysis
    • 30.2.4. International Business Machines Corporation Overview, Products and Services, Strategy and Financial Analysis
    • 30.2.5. Hewlett Packard Enterprise Overview, Products and Services, Strategy and Financial Analysis

31. Machine Learning Operations Market Other Major And Innovative Companies

  • 31.1. Statistical Analysis System (SAS )
  • 31.2. Databricks Inc.
  • 31.3. Cloudera Inc.
  • 31.4. Alteryx Inc.
  • 31.5. Comet
  • 31.6. GAVS Technologies
  • 31.7. DataRobot Inc.
  • 31.8. Veritone
  • 31.9. Dataiku
  • 31.10. Parallel LLC
  • 31.11. Neptune Labs
  • 31.12. SparkCognition
  • 31.13. Weights & Biases
  • 31.14. Kensho Technologies Inc.
  • 31.15. Akira.Al

32. Global Machine Learning Operations Market Competitive Benchmarking And Dashboard

33. Key Mergers And Acquisitions In The Machine Learning Operations Market

34. Recent Developments In The Machine Learning Operations Market

35. Machine Learning Operations Market High Potential Countries, Segments and Strategies

  • 35.1 Machine Learning Operations Market In 2029 - Countries Offering Most New Opportunities
  • 35.2 Machine Learning Operations Market In 2029 - Segments Offering Most New Opportunities
  • 35.3 Machine Learning Operations Market In 2029 - Growth Strategies
    • 35.3.1 Market Trend Based Strategies
    • 35.3.2 Competitor Strategies

36. Appendix

  • 36.1. Abbreviations
  • 36.2. Currencies
  • 36.3. Historic And Forecast Inflation Rates
  • 36.4. Research Inquiries
  • 36.5. The Business Research Company
  • 36.6. Copyright And Disclaimer