The Machine
Learning Operations Global Market Report 2024 by The Business Research Company
provides market overview across 60+ geographies in the seven regions -
Asia-Pacific, Western Europe, Eastern Europe, North America, South America, the
Middle East, and Africa, encompassing 27 major global industries. The report
presents a comprehensive analysis over a ten-year historic period (2010-2021)
and extends its insights into a ten-year forecast period (2023-2033).
Learn More On The Machine Learning Operations Market:
https://www.thebusinessresearchcompany.com/report/machine-learning-operations-global-market-report
According to The Business Research Company’s Machine Learning Operations Global
Market Report 2024, 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.
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.
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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
Major companies operating in the machine learning operations market are developing
new innovative solutions, such as managed machine learning platforms, to gain a
competitive edge in the market. Managed machine learning platform refers to a
comprehensive and integrated software solution that assists organizations in
developing, deploying, and managing machine learning (ML) models without
requiring users to handle the underlying infrastructure complexities. For
instance, in May 2021, Google LLC, a US-based technology company, launched
Vertex AI, a managed machine learning platform. This platform simplifies the
deployment and maintenance of AI models, requiring fewer lines of code for
training compared to other solutions. Vertex AI integrates various Google Cloud
services under a unified interface, accelerating the transition from model
experimentation to production. It includes MLOps features to enhance
experimentation, feature management, and model deployment. The platform is
designed to be accessible to data scientists of all skill levels, offering a
comprehensive solution for managing the end-to-end machine learning workflow
efficiently.
The machine learning operations market report table of contents includes:
1. Executive Summary
2. Market Characteristics
3. Market Trends And Strategies
4. Impact Of COVID-19
5. Market Size And Growth
6. Segmentation
7. Regional And Country Analysis
.
.
.
27. Competitive Landscape And Company Profiles
28. Key Mergers And Acquisitions
29. Future Outlook and Potential Analysis
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