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機械学習オペレーションの世界市場レポート 2024

Machine Learning Operations Global Market Report 2024

出版日: 受注後更新 | 発行: The Business Research Company | ページ情報: 英文 175 Pages | 納期: 2~10営業日

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機械学習オペレーションの世界市場レポート 2024
出版日: 受注後更新
発行: The Business Research Company
ページ情報: 英文 175 Pages
納期: 2~10営業日
  • 全表示
  • 概要
  • 目次
概要

機械学習オペレーションの市場規模は、今後数年間で急激に成長すると予想されています。 2028年には38.1%の年間複合成長率(CAGR)で78億5,000万米ドルに成長すると予想されます。予測期間中に予想される成長は、クラウドコンピューティングの台頭、さまざまな業界での機械学習の採用の増加、モデル展開テクノロジの開発、アジャイル開発手法の採用、および機械学習モデルの複雑さの増大に起因すると考えられます。予測期間中に予想される主な動向には、拡張分析の統合、機械学習の民主化、エッジ AIアプリケーションの急激な成長、自動ハイパーパラメーター調整、MLOpsパイプラインのセキュリティの強化などが含まれます。これらの動向が集合して、機械学習オペレーションの進化する情勢を形作ります。

自動運転車に対する需要の高まりにより、機械学習オペレーション(MLOps)市場の成長が促進される見込みです。自動運転車には高度なセンサー、カメラ、レーダー、ライダー、人工知能(AI)システムが装備されており、人間が直接介入することなく道路上でのナビゲーションや意思決定が可能になります。自動運転車のMLOpsには、車両内の機械学習モデルの継続的な統合、展開、管理が含まれます。これにより、センサーからのリアルタイムデータと多様な運転シナリオに基づいて運転能力を適応させ、向上させることができます。道路安全保険協会の2022年 12月の報告書によると、2025年までに推定350万台の自動運転車が米国の道路を走行すると予測されており、この数は2030年までに450万台に増加すると予想されています。自動車の運転は、機械学習運用市場の重要な推進力であると認識されています。

機械学習オペレーション市場の主要企業は、競争上の優位性を獲得するために、マネージド機械学習プラットフォームなどの革新的なソリューションの開発に注力しています。マネージド機械学習プラットフォームは、基盤となるインフラストラクチャの複雑さをユーザーが処理することなく、組織が機械学習(ML)モデルを開発、デプロイ、管理できるように支援する、包括的で統合されたソフトウェアソリューションです。米国に本拠を置くテクノロジー企業であるGoogle LLCは、2021年 5月のVertex AIの発売でこの傾向を実証しています。Vertex AIはAIモデルのデプロイとメンテナンスを簡素化し、他のソリューションと比較してトレーニングに必要なコード行が少なくなります。さまざまなGoogle Cloudサービスを統一インターフェースの下に統合し、モデルの実験から本番環境へのスムーズな移行を促進します。 MLOps機能により、Vertex AIは実験、機能管理、モデルのデプロイを強化し、あらゆるスキルレベルのデータサイエンティストに対応し、エンドツーエンドの機械学習ワークフローを管理するための効率的なソリューションを提供します。

目次

第1章 エグゼクティブサマリー

第2章 市場の特徴

第3章 市場動向と戦略

第4章 マクロ経済シナリオ

  • 高インフレが市場に与える影響
  • ウクライナ・ロシア戦争が市場に与える影響
  • COVID-19による市場への影響

第5章 世界市場規模と成長

  • 世界の市場促進要因と抑制要因
    • 市場促進要因
    • 市場抑制要因
  • 世界の市場規模実績と成長、2018年~2023年
  • 世界の市場規模予測と成長、2023年~2028年、2033年

第6章 市場セグメンテーション

  • 世界の機械学習オペレーション市場、展開タイプ別セグメンテーション、実績および予測、2018-2023年、2023-2028年、2033年
  • オンプレミス
  • クラウド
  • その他の展開
  • 世界の機械学習オペレーション市場、組織規模別のセグメンテーション、実績および予測、2018-2023年、2023-2028年、2033年
  • 大企業
  • 中小企業
  • 世界の機械学習オペレーション市場、業界別セグメンテーション、実績および予測、2018-2023年、2023-2028年、2033年
  • 銀行、金融サービス、保険(BFSI)
  • 製造業
  • ITとテレコム
  • 小売とeコマース
  • エネルギーとユーティリティ
  • ヘルスケア
  • メディアとエンターテイメント
  • その他の業界

第7章 地域および国の分析

  • 世界の機械学習オペレーション市場、地域別、実績および予測、2018-2023年、2023-2028年、2033年
  • 世界の機械学習オペレーション市場、国別、実績および予測、2018-2023年、2023-2028年、2033年

第8章 アジア太平洋市場

第9章 中国市場

第10章 インド市場

第11章 日本市場

第12章 オーストラリア市場

第13章 インドネシア市場

第14章 韓国市場

第15章 西欧市場

第16章 英国市場

第17章 ドイツ市場

第18章 フランス市場

第19章 イタリア市場

第20章 スペイン市場

第21章 東欧市場

第22章 ロシア市場

第23章 北米市場

第24章 米国市場

第25章 カナダ市場

第26章 南米市場

第27章 ブラジル市場

第28章 中東市場

第29章 アフリカ市場

第30章 競合情勢と企業プロファイル

  • 機械学習オペレーション市場の競合情勢
  • 機械学習オペレーション市場の企業プロファイル
    • Amazon.com Inc.
    • Alphabet Inc.
    • Microsoft Corporation
    • International Business Machines Corporation
    • Hewlett Packard Enterprise

第31章 その他の主要および革新的な企業

  • 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 競合ベンチマーキング

第33章 競合ダッシュボード

第34章 主要な合併と買収

第35章 将来の見通しと可能性の分析

第36章 付録

目次
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

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  • 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.
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  • 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