Machine Learning as a Service (MLaaS) industry, By Component (Software tools, Cloud APIs, Web-based APIs), By Application (Network analytics, Predictive maintenance, Augmented reality), By Deployment (Cloud, On Premise), By End-User (Manufacturing, Healthcare, BFSI, Transportation, Government, Retail)- Forecast 2027
Market Highlights
According to Market Research Future (MRFR), the global MLaaS Industry is projected to grow at USD 4630 million at a CAGR of 40% between 2016 and 2022 (forecast period). The study contains a COVID-19 review of the global machine learning as a service (MLaaS) market and provides a broad analysis of market segments, current trends, growth projections, and market challenges to assess market opportunities.
Machine learning as a service refers to a variety of services that provide machine learning tools as part of cloud computing services, including data visualization, APIs, face recognition, natural language processing, predictive analytics, and deep learning. The key benefit of machine learning as a service is that customers can get started easily with machine learning without downloading and installing any software at the end. Machine learning as a service offers services to developers, including data modeling APIs, machine learning algorithms, data transformations, and predictive analytics.
Market Dynamics
The increased volume of data and the variety of data to be handled qualitatively are significant factors impelling the MLaaS industry. Innovations in automation technology and the growing adoption of cloud-based systems are driving the growth of machine learning as a service industry. In addition to the availability of data storage at a cheaper rate, and the introduction of the Internet of Things (IoT), the market for machine learning as a service (MLaaS) is also expanding. The study shows that a lack of historical data is one of the major limiting factors in the development of machine learning as a service (MLaaS) market.
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Segmentation:
The market for machine learning as a service (MLaaS) has been segmented based on component, application, organization size, deployment, and end-user.
By component, the global machine learning as a service (MLaaS) market has been segmented into software tools, cloud-based APIs, and web-based APIs.
By application, the global market has been segmented into network analytics, predictive maintenance, augmented reality, marketing, and advertising, risk analytics and fraud detection, and others.
By organization size, the global market has been segmented into SMBs and large enterprises.
By deployment type, the global market has been segmented into the cloud and on-premise.
By the end-user, the global market has been segmented into manufacturing, BFSI, healthcare, retail, transportation, government, telecom, and others.
Regional Analysis
The geographical analysis of the global machine learning as a service (MLaaS) market is being examined for regions such as Europe, Asia Pacific, North America, and the Rest of the World.
The study shows that the North American region will dominate the market for machine learning as a service (MLaaS) over the forecast period, followed by Europe due to significant advances in the field of machine learning as a service seen in countries such as the United States and Canada. The study also shows that both the U.S. and Canada are the hub of large and start-up vendors in the North American region. The Asia Pacific countries like China, Japan, South Korea, India, and others are investing heavily in R&D. The Asia Pacific region will show a positive increase in the demand for machine learning as a service (MLaaS) over the forecast period.
Key Players
The prominent participants in the machine learning as a service (MLaaS) market are- Google (U.S.), BigML (U.S.), Microsoft (U.S.), AT&T (U.S.), IBM (U.S.), Amazon Web Services (U.S.), Yottamine Analytics (U.S.), Ersatz Labs, Inc. (U.S.), Fuzzy.ai (Canada), and Sift Science, Inc. (U.S.) among others.
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