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市場調查報告書
商品編碼
1455490

2024 年機器學習營運全球市場報告

Machine Learning Operations Global Market Report 2024

出版日期: 按訂單生產 | 出版商: The Business Research Company | 英文 175 Pages | 商品交期: 2-10個工作天內

價格
簡介目錄

機器學習業務的市場規模預計在未來幾年將快速成長。預計到 2028 年將以 38.1% 的複合年成長率 (CAGR) 成長至 78.5 億美元。預測期內的預期成長是由於雲端運算的興起、各行業擴大採用機器學習、模型部署技術的發展、敏捷開發方法的採用以及機器學習模型複雜性的增加。由於此。預測期內預計的主要趨勢包括增強分析的整合、機器學習的民主化、邊緣人工智慧應用的快速成長、自動超參數調整以及 MLOps 管道的增強安全性。總的來說,這些趨勢將塑造機器學習操作不斷發展的模式。

對自動駕駛汽車的需求不斷成長預計將推動機器學習操作(MLOps)市場的成長。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,使它們能夠在道路上導航並做出決策,而無需人工直接干預。自動駕駛車輛的 MLOps 涉及車輛內機器學習模型的持續整合、部署和管理。這使您可以根據感測器的即時資料和不同的駕駛場景來調整和提高駕駛性能。根據公路安全保險協會 2022 年 12 月的報告,預計到 2025 年,美國道路上將有 350 萬輛自動駕駛汽車,到 2030 年,這一數字將增至 450 萬輛,預計還會增加。駕駛被認為是機器學習營運市場的關鍵驅動力。

機器學習營運市場的主要企業專注於開發創新解決方案,例如託管機器學習平台,以獲得競爭優勢。託管機器學習平台是一種全面的整合軟體解決方案,可協助組織開發、部署和管理機器學習 (ML) 模型,而無需使用者處理底層基礎架構的複雜性。美國科技公司 Google LLC 於 2021 年 5 月推出 Vertex AI,展示了這一趨勢。 Vertex AI 簡化了 AI 模型的部署和維護,與其他解決方案相比,訓練所需的程式碼行更少。它將各種 Google Cloud 服務整合在統一的介面下,促進從模型實驗到生產的平穩過渡。憑藉 MLOps 功能,Vertex AI 為實驗、功能管理和模型部署提供支持,以適應各種技能水平的資料科學家,並為管理端到端機器學習工作流程提供有效的解決方案。

目錄

第1章執行摘要

第2章 市場特點

第3章 市場趨勢與策略

第4章宏觀經濟情景

  • 高通膨對市場的影響
  • 烏克蘭與俄羅斯戰爭對市場的影響
  • COVID-19 對市場的影響

第5章世界市場規模與成長

  • 全球市場促進因素與限制因素
    • 市場促進因素
    • 市場限制因素
  • 2018-2023 年全球市場規模表現與成長
  • 全球市場規模預測與成長,2023-2028、2033

第6章市場區隔

  • 全球機器學習營運市場,按部署類型細分、實際和預測,2018-2023、2023-2028、2033
  • 本地
  • 其他進展
  • 全球機器學習營運市場,依組織規模細分、實際及預測,2018-2023、2023-2028、2033
  • 主要企業
  • 中小企業
  • 全球機器學習營運市場,依產業細分、實際及預測,2018-2023、2023-2028、2033
  • 銀行、金融服務和保險 (BFSI)
  • 製造業
  • 資訊科技和電信
  • 零售與電子商務
  • 能源和公共事業
  • 衛生保健
  • 媒體與娛樂
  • 其他行業

第 7 章 區域與國家分析

  • 全球機器學習營運市場,按地區、實際和預測,2018-2023、2023-2028、2033
  • 全球機器學習營運市場,依國家、實際及預測,2018-2023、2023-2028、2033

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 競爭格局及公司概況

  • 機器學習營運市場競爭格局
  • 機器學習營運市場公司簡介
    • Amazon.com Inc.
    • Alphabet Inc.
    • Microsoft Corporation
    • International Business Machines Corporation
    • Hewlett Packard Enterprise

第31章 其他重大及創新企業

  • 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章競爭基準化分析

第 33 章. 競爭對手儀表板

第34章 重大併購

第35章 未來前景與可能性分析

第36章附錄

簡介目錄
Product Code: r16491

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 $1.56 billion in 2023 to $2.16 billion in 2024 at a compound annual growth rate (CAGR) of 38.4%. The growth observed in the historic period can be attributed to several factors, including the increasing complexity of machine learning models, the rapid evolution of edge computing, the rising adoption of federated learning, the continuous integration of DevOps and MLOps practices, and a surge in the adoption of automated machine learning (AutoML). These trends collectively contributed to the development and expansion of Machine Learning Operations during that period.

The machine learning operations market size is expected to see exponential growth in the next few years. It will grow to $7.85 billion in 2028 at a compound annual growth rate (CAGR) of 38.1%. The anticipated growth in the forecast period can be attributed to the rise of cloud computing, increased adoption of machine learning across various industries, the development of model deployment technologies, the adoption of agile development practices, and the increased complexity of machine learning models. Major trends expected in the forecast period include the integration of augmented analytics, the democratization of machine learning, exponential growth in edge AI applications, automated hyperparameter tuning, and the enhancement of security in MLOps pipelines. These trends collectively shape the evolving landscape of Machine Learning Operations.

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.

Key players in the machine learning operations market are focusing on developing innovative solutions, such as managed machine learning platforms, to gain a competitive advantage. A managed machine learning platform is a comprehensive and integrated software solution that assists organizations in developing, deploying, and managing machine learning (ML) models without the need for users to handle the complexities of underlying infrastructure. Google LLC, a US-based technology company, exemplifies this trend with the launch of Vertex AI in May 2021. Vertex AI simplifies the deployment and maintenance of AI models, requiring fewer lines of code for training compared to other solutions. It integrates various Google Cloud services under a unified interface, facilitating a smooth transition from model experimentation to production. With MLOps features, Vertex AI enhances experimentation, feature management, and model deployment, catering to data scientists of all skill levels and offering an efficient solution for managing the end-to-end machine learning workflow.

In June 2021, Hewlett Packard Enterprise, a US-based information technology company, strategically acquired Determined.AI Inc. for an undisclosed amount. This acquisition strengthens HPE's capabilities in the machine learning domain, enabling the integration of Determined AI's powerful open-source platform into HPE's AI and high-performance computing offerings. The move empowers ML engineers to efficiently train models and extract faster and more accurate insights across various industries. Determined.AI Inc., a US-based software company, is recognized for providing an open-source machine learning platform.

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 2023. 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 2024 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 50+ geographies.
  • Understand how the market has been affected by the coronavirus and how it is responding as the impact of the virus abates.
  • Assess the Russia - Ukraine war's impact on agriculture, energy and mineral commodity supply and its direct and indirect impact on the market.
  • Measure the impact of high global inflation on market growth.
  • 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 3-5 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? 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 impact of sanctions, supply chain disruptions, and altered demand for goods and services due to the Russian Ukraine war, impacting various macro-economic factors and parameters in the Eastern European region and its subsequent effect on global markets.

The impact of higher inflation in many countries and the resulting spike in interest rates.

The continued but declining impact of covid 19 on supply chains and consumption patterns.

  • 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
  • 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

  • 4.1. Impact Of High Inflation On The Market
  • 4.2. Ukraine-Russia War Impact On The Market
  • 4.3. COVID-19 Impact On The Market

5. Global Machine Learning Operations Market Size and Growth

  • 5.1. Global Machine Learning Operations Market Drivers and Restraints
    • 5.1.1. Drivers Of The Market
    • 5.1.2. Restraints Of The Market
  • 5.2. Global Machine Learning Operations Historic Market Size and Growth, 2018 - 2023, Value ($ Billion)
  • 5.3. Global Machine Learning Operations Forecast Market Size and Growth, 2023 - 2028, 2033F, Value ($ Billion)

6. Machine Learning Operations Market Segmentation

  • 6.1. Global Machine Learning Operations Market, Segmentation By Deployment Type, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • On-premise
  • Cloud
  • Other Deployments
  • 6.2. Global Machine Learning Operations Market, Segmentation By Organization Size, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • Large Enterprises
  • Small and Medium-sized Enterprises
  • 6.3. Global Machine Learning Operations Market, Segmentation By Industry Vertical, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • Banking, Financial Services, and Insurance (BFSI)
  • Manufacturing
  • IT and Telecom
  • Retail and E-commerce
  • Energy and Utility
  • Healthcare
  • Media and Entertainment
  • Other Industry Verticals

7. Machine Learning Operations Market Regional And Country Analysis

  • 7.1. Global Machine Learning Operations Market, Split By Region, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 7.2. Global Machine Learning Operations Market, Split By Country, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion

8. Asia-Pacific Machine Learning Operations Market

  • 8.1. Asia-Pacific Machine Learning Operations Market Overview
  • Region Information, Impact Of COVID-19, 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, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 8.3. Asia-Pacific Machine Learning Operations Market, Segmentation By Organization Size, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 8.4. Asia-Pacific Machine Learning Operations Market, Segmentation By Industry Vertical, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ 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, 2018-2023, 2023-2028F, 2033F,$ Billion
  • 9.3. China Machine Learning Operations Market, Segmentation By Organization Size, Historic and Forecast, 2018-2023, 2023-2028F, 2033F,$ Billion
  • 9.4. China Machine Learning Operations Market, Segmentation By Industry Vertical, Historic and Forecast, 2018-2023, 2023-2028F, 2033F,$ Billion

10. India Machine Learning Operations Market

  • 10.1. India Machine Learning Operations Market, Segmentation By Deployment Type, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 10.2. India Machine Learning Operations Market, Segmentation By Organization Size, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 10.3. India Machine Learning Operations Market, Segmentation By Industry Vertical, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ 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, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 11.3. Japan Machine Learning Operations Market, Segmentation By Organization Size, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 11.4. Japan Machine Learning Operations Market, Segmentation By Industry Vertical, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion

12. Australia Machine Learning Operations Market

  • 12.1. Australia Machine Learning Operations Market, Segmentation By Deployment Type, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 12.2. Australia Machine Learning Operations Market, Segmentation By Organization Size, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 12.3. Australia Machine Learning Operations Market, Segmentation By Industry Vertical, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion

13. Indonesia Machine Learning Operations Market

  • 13.1. Indonesia Machine Learning Operations Market, Segmentation By Deployment Type, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 13.2. Indonesia Machine Learning Operations Market, Segmentation By Organization Size, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 13.3. Indonesia Machine Learning Operations Market, Segmentation By Industry Vertical, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ 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, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 14.3. South Korea Machine Learning Operations Market, Segmentation By Organization Size, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 14.4. South Korea Machine Learning Operations Market, Segmentation By Industry Vertical, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ 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, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 15.3. Western Europe Machine Learning Operations Market, Segmentation By Organization Size, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 15.4. Western Europe Machine Learning Operations Market, Segmentation By Industry Vertical, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion

16. UK Machine Learning Operations Market

  • 16.1. UK Machine Learning Operations Market, Segmentation By Deployment Type, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 16.2. UK Machine Learning Operations Market, Segmentation By Organization Size, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 16.3. UK Machine Learning Operations Market, Segmentation By Industry Vertical, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion

17. Germany Machine Learning Operations Market

  • 17.1. Germany Machine Learning Operations Market, Segmentation By Deployment Type, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 17.2. Germany Machine Learning Operations Market, Segmentation By Organization Size, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 17.3. Germany Machine Learning Operations Market, Segmentation By Industry Vertical, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion

18. France Machine Learning Operations Market

  • 18.1. France Machine Learning Operations Market, Segmentation By Deployment Type, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 18.2. France Machine Learning Operations Market, Segmentation By Organization Size, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 18.3. France Machine Learning Operations Market, Segmentation By Industry Vertical, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion

19. Italy Machine Learning Operations Market

  • 19.1. Italy Machine Learning Operations Market, Segmentation By Deployment Type, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 19.2. Italy Machine Learning Operations Market, Segmentation By Organization Size, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 19.3. Italy Machine Learning Operations Market, Segmentation By Industry Vertical, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion

20. Spain Machine Learning Operations Market

  • 20.1. Spain Machine Learning Operations Market, Segmentation By Deployment Type, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 20.2. Spain Machine Learning Operations Market, Segmentation By Organization Size, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 20.3. Spain Machine Learning Operations Market, Segmentation By Industry Vertical, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ 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, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 21.3. Eastern Europe Machine Learning Operations Market, Segmentation By Organization Size, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 21.4. Eastern Europe Machine Learning Operations Market, Segmentation By Industry Vertical, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion

22. Russia Machine Learning Operations Market

  • 22.1. Russia Machine Learning Operations Market, Segmentation By Deployment Type, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 22.2. Russia Machine Learning Operations Market, Segmentation By Organization Size, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 22.3. Russia Machine Learning Operations Market, Segmentation By Industry Vertical, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ 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, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 23.3. North America Machine Learning Operations Market, Segmentation By Organization Size, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 23.4. North America Machine Learning Operations Market, Segmentation By Industry Vertical, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ 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, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 24.3. USA Machine Learning Operations Market, Segmentation By Organization Size, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 24.4. USA Machine Learning Operations Market, Segmentation By Industry Vertical, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ 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, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 25.3. Canada Machine Learning Operations Market, Segmentation By Organization Size, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 25.4. Canada Machine Learning Operations Market, Segmentation By Industry Vertical, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ 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, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 26.3. South America Machine Learning Operations Market, Segmentation By Organization Size, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 26.4. South America Machine Learning Operations Market, Segmentation By Industry Vertical, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion

27. Brazil Machine Learning Operations Market

  • 27.1. Brazil Machine Learning Operations Market, Segmentation By Deployment Type, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 27.2. Brazil Machine Learning Operations Market, Segmentation By Organization Size, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 27.3. Brazil Machine Learning Operations Market, Segmentation By Industry Vertical, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ 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, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 28.3. Middle East Machine Learning Operations Market, Segmentation By Organization Size, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 28.4. Middle East Machine Learning Operations Market, Segmentation By Industry Vertical, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ 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, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 29.3. Africa Machine Learning Operations Market, Segmentation By Organization Size, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 29.4. Africa Machine Learning Operations Market, Segmentation By Industry Vertical, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ 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.
      • 30.2.1.1. Overview
      • 30.2.1.2. Products and Services
      • 30.2.1.3. Strategy
      • 30.2.1.4. Financial Performance
    • 30.2.2. Alphabet Inc.
      • 30.2.2.1. Overview
      • 30.2.2.2. Products and Services
      • 30.2.2.3. Strategy
      • 30.2.2.4. Financial Performance
    • 30.2.3. Microsoft Corporation
      • 30.2.3.1. Overview
      • 30.2.3.2. Products and Services
      • 30.2.3.3. Strategy
      • 30.2.3.4. Financial Performance
    • 30.2.4. International Business Machines Corporation
      • 30.2.4.1. Overview
      • 30.2.4.2. Products and Services
      • 30.2.4.3. Strategy
      • 30.2.4.4. Financial Performance
    • 30.2.5. Hewlett Packard Enterprise
      • 30.2.5.1. Overview
      • 30.2.5.2. Products and Services
      • 30.2.5.3. Strategy
      • 30.2.5.4. Financial Performance

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

33. Global Machine Learning Operations Market Competitive Dashboard

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

35. Machine Learning Operations Market Future Outlook and Potential Analysis

  • 35.1 Machine Learning Operations Market In 2028 - Countries Offering Most New Opportunities
  • 35.2 Machine Learning Operations Market In 2028 - Segments Offering Most New Opportunities
  • 35.3 Machine Learning Operations Market In 2028 - 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