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市場調查報告書
商品編碼
1847610

2025年全球機器學習營運市場報告

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個工作天內

價格
簡介目錄

近年來，機器學習維運市場呈指數級成長，從2024年的21.6億美元成長到2025年的29.7億美元，複合年成長率達37.5%。這一成長主要受以下因素驅動：機器學習模型的日益複雜化、邊緣運算的快速發展、聯邦學習的日益普及、DevOps與MLOPs的持續融合以及AutoML應用的激增。

預計未來幾年機器學習維運市場將呈指數級成長，到2029年市場規模將達到107.1億美元，年複合成長率（CAGR）高達37.8%。預測期內的成長主要歸功於雲端運算的興起、機器學習在工業領域的應用日益廣泛、模型部署技術的進步、敏捷開發實踐的普及以及機器學習模型複雜性的不斷提升。預測期內的關鍵趨勢包括：分析整合度的提高、機器學習的普及化、邊緣人工智慧應用的指數級成長、自動化超參數調優以及機器學習運維管道安全性的增強。

未來五年37.8%的成長預測較我們先前的預測略微下調了0.2%。這一下調主要歸因於美國與其他國家之間的關稅影響。關稅可能會影響國際採購的高效能GPU和容器編配系統的可用性，從而推高機器學習工作流程的營運成本，而這些設備對於訓練和維護機器學習模型至關重要。由於相互關稅以及日益加劇的貿易緊張局勢和限制對全球經濟和貿易的負面影響，這種影響可能會更加廣泛。

對自動駕駛汽車日益成長的需求有望推動機器學習維運（MLOps）市場的發展。自動駕駛汽車配備了先進的感測器、攝影機、雷達、LiDAR和人工智慧（AI）系統，使其能夠在無需人工干預的情況下自主導航和做出道路決策。自動駕駛汽車的MLOps涉及機器學習模型在車輛內部的持續整合、部署和管理，使其能夠根據來自感測器和各種駕駛場景的即時數據來調整和改進其駕駛能力。根據美國公路安全保險美國）2022年12月發布的報告，預計到2025年，美國道路上將有350萬輛自動駕駛汽車，到2030年，這一數字預計將增加至450萬輛。自動駕駛汽車需求的激增被認為是機器學習維運市場發展的關鍵促進因素。

目錄

第1章執行摘要

第2章 市場特徵

第3章 市場趨勢與策略

第4章 市場：宏觀經濟情景，包括利率、通貨膨脹、地緣政治、貿易戰和關稅，以及新冠疫情及其復甦對市場的影響

第5章 全球成長分析與策略分析框架

  • 全球機器學習營運：PESTEL 分析（政治、社會、技術、環境、法律因素、促進因素和限制因素）
  • 終端用戶產業分析
  • 全球機器學習營運市場：成長率分析
  • 全球機器學習營運市場表現：規模與成長，2019-2024 年
  • 全球機器學習營運市場預測：規模與成長，2024-2029年，2034年預測
  • 全球機器學習業務：潛在市場規模 (TAM)

第6章 市場細分

  • 全球機器學習維運市場：依部署類型分類，實際值與預測值，2019-2024 年、2024-2029 年預測值、2034 年預測值
  • 本地部署
  • 雲
  • 其他部署類型
  • 全球機器學習營運市場：依組織規模分類，實際結果與預測，2019-2024 年、2024-2029 年預測、2034 年預測
  • 主要企業
  • 小型企業
  • 全球機器學習營運市場：依產業分類，實際結果與預測，2019-2024年、2024-2029年預測、2034年預測
  • 銀行、金融服務和保險業 (BFSI)
  • 製造業
  • 資訊科技和通訊
  • 零售與電子商務
  • 能源與公用事業
  • 衛生保健
  • 媒體與娛樂
  • 其他行業
  • 全球機器學習維運市場：細分市場（按類型分類，包括本地部署），實際數據和預測數據，2019-2024 年、2024-2029 年預測數據、2034 年預測數據
  • 私人資料中心
  • 本地伺服器
  • 全球機器學習維運市場：按雲端平台、類型、實際值和預測值細分，2019-2024 年、2024-2029 年預測值、2034 年預測值
  • 公共雲端服務
  • 混合雲端解決方案
  • 多重雲端環境
  • 全球機器學習維運市場：細分市場及其他部署類型（按類型分類），實際值及預測值，2019-2024年，2024-2029年預測值，2034年預測值
  • 邊緣配置
  • 混合型本地部署或雲端解決方案

第7章 區域和國家分析

  • 全球機器學習營運市場：依地區分類，實際結果與預測，2019-2024年、2024-2029年預測、2034年預測
  • 全球機器學習營運市場：按國家/地區分類，實際結果和預測，2019-2024 年、2024-2029 年預測、2034 年預測

第8章 亞太市場

第9章：中國市場

第10章 印度市場

第11章 日本市場

第12章：澳洲市場

第13章 印尼市場

第14章 韓國市場

第15章 西歐市場

第16章英國市場

第17章：德國市場

第18章：法國市場

第19章：義大利市場

第20章：西班牙市場

第21章 東歐市場

第22章 俄羅斯市場

第23章 北美市場

第24章美國市場

第25章：加拿大市場

第26章 南美洲市場

第27章：巴西市場

第28章 中東市場

第29章：非洲市場

第30章：競爭格局與公司概況

  • 機器學習營運市場：競爭格局
  • 機器學習營運市場：公司概況
    • 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：其他領先和創新企業

  • 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 全球市場競爭基準化分析與儀錶板

第33章 重大併購

第34章 近期市場趨勢

第35章：高潛力市場國家、細分市場與策略

  • 2029年機器學習營運市場：提供新機會的國家
  • 2029年機器學習營運市場：新興細分市場機會
  • 機器學習營運市場 2029：成長策略
    • 基於市場趨勢的策略
    • 競爭對手策略

第36章附錄

簡介目錄
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

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  • 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