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市场调查报告书
商品编码
1455490

2024 年机器学习营运全球市场报告

Machine Learning Operations Global Market Report 2024
出版日期: 按订单生产 | 出版商: The Business Research Company | 英文 175 Pages | 商品交期: 2-10个工作天内

价格
简介目录

机器学习业务的市场规模预计在未来几年将快速成长。预计到 2028 年将以 38.1% 的复合年增长率 (CAGR) 增长至 78.5 亿美元。预测期内的预期增长是由于云端运算的兴起、各行业越来越多地采用机器学习、模型部署技术的发展、敏捷开发方法的采用以及机器学习模型复杂性的增加。由于此。预测期内预计的主要趋势包括增强分析的整合、机器学习的民主化、边缘人工智慧应用的快速增长、自动超参数调整以及 MLOps 管道的增强安全性。总的来说，这些趋势将塑造机器学习操作不断发展的模式。

对自动驾驶汽车的需求不断增长预计将推动机器学习操作（MLOps）市场的成长。自动驾驶汽车配备了先进的传感器、摄影机、雷达、光达和人工智慧 (AI) 系统，使它们能够在道路上导航并做出决策，而无需人工直接干预。自动驾驶车辆的 MLOps 涉及车辆内机器学习模型的持续整合、部署和管理。这使您可以根据感测器的即时资料和不同的驾驶场景来调整和提高驾驶性能。根据公路安全保险协会 2022 年 12 月的报告，预计到 2025 年，美国道路上将有 350 万辆自动驾驶汽车，到 2030 年，这一数字将增至 450 万辆，预计还会增加。驾驶被认为是机器学习营运市场的关键驱动力。

机器学习营运市场的主要企业专注于开发创新解决方案，例如託管机器学习平台，以获得竞争优势。託管机器学习平台是一种全面的整合软体解决方案，可协助组织开发、部署和管理机器学习 (ML) 模型，而无需使用者处理底层基础架构的复杂性。美国科技公司 Google LLC 于 2021 年 5 月推出 Vertex AI，展示了这一趋势。 Vertex AI 简化了 AI 模型的部署和维护，与其他解决方案相比，训练所需的程式码行更少。它将各种 Google Cloud 服务整合在统一的介面下，促进从模型实验到生产的平稳过渡。凭藉 MLOps 功能，Vertex AI 为实验、功能管理和模型部署提供支持，以适应各种技能水平的资料科学家，并为管理端到端机器学习工作流程提供有效的解决方案。

目录

第一章执行摘要

第二章 市场特点

第三章 市场趋势与策略

第四章宏观经济情景

  • 高通膨对市场的影响
  • 乌克兰与俄罗斯战争对市场的影响
  • COVID-19 对市场的影响

第五章世界市场规模与成长

  • 全球市场驱动因素与限制因素
    • 市场驱动因素
    • 市场限制因素
  • 2018-2023 年全球市场规模表现与成长
  • 全球市场规模预测与成长，2023-2028、2033

第六章市场区隔

  • 全球机器学习营运市场，按部署类型细分、实际和预测，2018-2023、2023-2028、2033
  • 本地
  • 云
  • 其他进展
  • 全球机器学习营运市场，依组织规模细分、实际及预测，2018-2023、2023-2028、2033
  • 大公司
  • 中小企业
  • 全球机器学习营运市场，依产业细分、实际及预测，2018-2023、2023-2028、2033
  • 银行、金融服务和保险 (BFSI)
  • 製造业
  • 资讯科技和电信
  • 零售与电子商务
  • 能源和公共事业
  • 卫生保健
  • 媒体与娱乐
  • 其他行业

第 7 章 区域与国家分析

  • 全球机器学习营运市场，按地区、实际和预测，2018-2023、2023-2028、2033
  • 全球机器学习营运市场，依国家、实际及预测，2018-2023、2023-2028、2033

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14章 韩国市场

第十五章 西欧市场

第十六章英国市场

第十七章 德国市场

第十八章 法国市场

第十九章 义大利市场

第20章 西班牙市场

第21章 东欧市场

第22章 俄罗斯市场

第23章 北美市场

第24章美国市场

第25章加拿大市场

第26章 南美洲市场

第27章 巴西市场

第28章 中东市场

第29章 非洲市场

第三十章 竞争格局及公司概况

  • 机器学习营运市场竞争格局
  • 机器学习营运市场公司简介
    • Amazon.com Inc.
    • Alphabet Inc.
    • Microsoft Corporation
    • International Business Machines Corporation
    • Hewlett Packard Enterprise

第三十一章 其他重大及创新企业

  • 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章竞争基准化分析

第 33 章. 竞争对手仪表板

第三十四章 重大併购

第35章 未来前景与可能性分析

第36章附录

简介目录
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