Overview and Scope
Machine learning operations refers to a set of practices and tools that automate and manage the lifecycle of machine learning models from development and training. It is used for a multitude of tasks related to deploying, managing, and monitoring machine learning models in production environments.
Sizing and Forecast
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 in the historic period can be attributed to increasing complexity of ml models, rapid evolution of edge computing, increasing adoption of federated learning, ontinuous integration of devops and mlops, surge in automl adoption.
The machine learning operations market size is expected to see exponential growth in the next few years. It will grow to $7.85 billion in 2028 at a compound annual growth rate (CAGR) of 38.1%. The growth in the forecast period can be attributed to rise of cloud computing, increased adoption of machine learning in industries, development of model deployment technologies, adoption of agile development practices, increased complexity of machine learning models. Major trends in the forecast period include augmented analytics integration, democratization of machine learning, exponential growth in edge ai applications, automated hyperparameter tuning, enhanced security in mlops pipelines.
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Segmentation & Regional Insights
The machine learning operations market covered in this report is segmented –
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
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.
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Major Driver Impacting Market Growth
The rising demand for self-driving cars is expected to propel the growth of the machine-learning operations market going forward. Self-driving cars are automobiles equipped with advanced sensors, cameras, radar, lidar, and artificial intelligence (AI) systems that enable them to navigate, operate, and make decisions on the road without direct human intervention. Machine learning operations (MLOps) in self-driving cars involve the continuous integration, deployment, and management of machine learning models within the vehicles, enabling them to adapt and improve their driving capabilities based on real-time data from sensors and diverse driving scenarios. For instance, in December 2022, according to a report published by the Insurance Institute for Highway Safety, a US-based non-profit organization, it is projected that there will be an estimated 3.5 million autonomous vehicles on American roads by 2025, with expectations for this number to increase to 4.5 million by the year 2030. Therefore, the rising demand for self-driving cars is driving the growth of the machine-learning operations market.
Key Industry Players
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
The machine learning operations market report table of contents includes:
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
5. Global Machine Learning Operations Market Size and Growth
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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
36. Appendix
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