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市场调查报告书
商品编码
1847610

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 250 Pages | 商品交期: 2-10个工作天内

价格
简介目录

近年来，机器学习维运市场呈指数级成长，从2024年的21.6亿美元成长到2025年的29.7亿美元，复合年增长率达37.5%。这一增长主要受以下因素驱动：机器学习模型的日益复杂化、边缘运算的快速发展、联邦学习的日益普及、DevOps与MLOPs的持续融合以及AutoML应用的激增。

预计未来几年机器学习维运市场将呈指数级成长，到2029年市场规模将达到107.1亿美元，年复合成长率（CAGR）高达37.8%。预测期内的成长主要归功于云端运算的兴起、机器学习在工业领域的应用日益广泛、模型部署技术的进步、敏捷开发实践的普及以及机器学习模型复杂性的不断提升。预测期内的关键趋势包括：分析整合度的提高、机器学习的普及化、边缘人工智慧应用的指数级增长、自动化超参数调优以及机器学习运维管道安全性的增强。

未来五年37.8%的成长预测较我们先前的预测略微下调了0.2%。这一下调主要归因于美国与其他国家之间的关税影响。关税可能会影响国际采购的高效能GPU和容器编配系统的可用性，从而推高机器学习工作流程的营运成本，而这些设备对于训练和维护机器学习模型至关重要。由于相互关税以及日益加剧的贸易紧张局势和限制对全球经济和贸易的负面影响，这种影响可能会更加广泛。

对自动驾驶汽车日益增长的需求有望推动机器学习维运（MLOps）市场的发展。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，使其能够在无需人工干预的情况下自主导航和做出道路决策。自动驾驶汽车的MLOps涉及机器学习模型在车辆内部的持续整合、部署和管理，使其能够根据来自感测器和各种驾驶场景的即时数据来调整和改进其驾驶能力。根据美国公路安全保险美国）2022年12月发布的报告，预计到2025年，美国道路上将有350万辆自动驾驶汽车，到2030年，这一数字预计将增加至450万辆。自动驾驶汽车需求的激增被认为是机器学习维运市场发展的关键驱动因素。

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、通货膨胀、地缘政治、贸易战和关税，以及新冠疫情及其復苏对市场的影响

第五章 全球成长分析与策略分析框架

  • 全球机器学习营运：PESTEL 分析（政治、社会、技术、环境、法律因素、驱动因素和限制因素）
  • 终端用户产业分析
  • 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 年
  • 全球机器学习营运市场预测：规模与成长，2024-2029年，2034年预测
  • 全球机器学习业务：潜在市场规模 (TAM)

第六章 市场细分

  • 全球机器学习维运市场：依部署类型划分，实际值与预测值，2019-2024 年、2024-2029 年预测值、2034 年预测值
  • 本地部署
  • 云
  • 其他部署类型
  • 全球机器学习营运市场：依组织规模划分，实际结果与预测，2019-2024 年、2024-2029 年预测、2034 年预测
  • 大公司
  • 小型企业
  • 全球机器学习营运市场：依产业划分，实际结果与预测，2019-2024年、2024-2029年预测、2034年预测
  • 银行、金融服务和保险业 (BFSI)
  • 製造业
  • 资讯科技和通讯
  • 零售与电子商务
  • 能源与公用事业
  • 卫生保健
  • 媒体与娱乐
  • 其他行业
  • 全球机器学习维运市场：细分市场（按类型划分，包括本地部署），实际数据和预测数据，2019-2024 年、2024-2029 年预测数据、2034 年预测数据
  • 私人资料中心
  • 本地伺服器
  • 全球机器学习维运市场：按云端平台、类型、实际值和预测值细分，2019-2024 年、2024-2029 年预测值、2034 年预测值
  • 公共云端服务
  • 混合云端解决方案
  • 多重云端环境
  • 全球机器学习维运市场：细分市场及其他部署类型（按类型划分），实际值及预测值，2019-2024年，2024-2029年预测值，2034年预测值
  • 边缘配置
  • 混合型本地部署或云端解决方案

第七章 区域和国家分析

  • 全球机器学习营运市场：依地区划分，实际结果与预测，2019-2024年、2024-2029年预测、2034年预测
  • 全球机器学习营运市场：按国家/地区划分，实际结果和预测，2019-2024 年、2024-2029 年预测、2034 年预测

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

第二十章：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

第三十章：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：公司概况
    • 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：其他领先和创新企业

  • 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錶板

第33章 重大併购

第34章 近期市场趋势

第35章：高潜力市场国家、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：新兴细分市场机会
  • 机器学习营运市场 2029：成长策略
    • 基于市场趋势的策略
    • 竞争对手策略

第36章附录

简介目录
Product Code: r28448u

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.

Note that the outlook for this market is being affected by rapid changes in trade relations and tariffs globally. The report will be updated prior to delivery to reflect the latest status, including revised forecasts and quantified impact analysis. The report's Recommendations and Conclusions sections will be updated to give strategies for entities dealing with the fast-moving international environment.

The sharp rise in U.S. tariffs and the ensuing trade tensions in spring 2025 are having a significant impact on the information technology sector, especially in hardware manufacturing, data infrastructure, and software deployment. Increased duties on imported semiconductors, circuit boards, and networking equipment have driven up production and operating costs for tech companies, cloud service providers, and data centers. Firms that depend on globally sourced components for laptops, servers, and consumer electronics are grappling with extended lead times and mounting pricing pressures. At the same time, tariffs on specialized software and retaliatory actions by key international markets have disrupted global IT supply chains and dampened foreign demand for U.S.-made technologies. In response, the sector is ramping up investments in domestic chip production, broadening its supplier network, and leveraging AI-powered automation to improve resilience and manage costs more effectively.

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 $2.97 billion in 2025 at a compound annual growth rate (CAGR) of 37.5%. 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 $10.71 billion in 2029 at a compound annual growth rate (CAGR) of 37.8%. 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 forecast of 37.8% growth over the next five years reflects a slight reduction of 0.2% from the previous projection. This reduction is primarily due to the impact of tariffs between the US and other countries. Tariffs could escalate operational expenses in ML workflows by impacting the availability of high-performance GPUs and container orchestration systems sourced internationally, crucial for training and maintaining ML models. The effect will also be felt more widely due to reciprocal tariffs and the negative effect on the global economy and trade due to increased trade tensions and restrictions.

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.

Reasons to Purchase

  • Gain a truly global perspective with the most comprehensive report available on this market covering 15 geographies.
  • Assess the impact of key macro factors such as geopolitical conflicts, trade policies and tariffs, post-pandemic supply chain realignment, inflation and interest rate fluctuations, and evolving regulatory landscapes.
  • Create regional and country strategies on the basis of local data and analysis.
  • Identify growth segments for investment.
  • Outperform competitors using forecast data and the drivers and trends shaping the market.
  • Understand customers based on the latest market shares.
  • Benchmark performance against key competitors.
  • Suitable for supporting your internal and external presentations with reliable high quality data and analysis
  • Report will be updated with the latest data and delivered to you within 2-3 working days of order along with an Excel data sheet for easy data extraction and analysis.
  • All data from the report will also be delivered in an excel dashboard format.

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, including technological disruption, regulatory shifts, and changing consumer preferences? 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 technological advancements such as AI and automation, Russia-Ukraine war, trade tariffs (government-imposed import/export duties), elevated inflation and interest rates.

  • 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.
  • 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; 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
  • 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, Trade Wars and Tariffs, And Covid And Recovery On The Market

  • 4.1. Supply Chain Impact from Tariff War & Trade Protectionism

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