India – March 16, 2022 —
Market Scenario:
Machine learning as a service refers to a range of services which offer machine learning tools as a part of cloud computing services, these tools include data visualization, APIs, face recognition, natural language processing, predictive analytics and deep learning. The main advantage of machine learning as a service is that customer can get started quickly with machine learning without downloading and installing any software at their end. Machine learning as a service delivers developers services which include data modeling APIs, machine learning algorithms, data transformations and predictive analytics.
The increased volume of data and diverse data to be handled qualitatively, are major factors driving the growth of Machine Learning as a Service (MLaaS) market. The innovations in automation technologies and increasing adoption of cloud-based systems is boosting the growth of machine learning as a service market. Apart from it availability of data storage at a cheaper rate and adoption of Internet of Things (IoT) is also driving the MLaaS market. The study indicates that lack the historical data is one of the major restraining factor in the growth of machine learning as a service (MLaaS) market.
Machine learning as a Service (MLaaS) market is segmented on the basis component, application, organization size, deployment and end-user. It has been observed that adoption of cloud technologies has become worldwide, this has resulted in increase of demand for cloud-based machine learning as a service (MLaaS).
The global Machine Learning As A Service (Mlaas) Market is expected to grow at USD ~4630 Million by 2022, at ~40% of CAGR between 2016 and 2022.
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Key Players
The prominent players in the machine learning as a service (MLaaS) Market are- Google (U.S.), BigML (U.S.), Microsoft (U.S.), IBM (U.S.), Amazon Web Services (U.S.), AT&T (U.S.), Fuzzy.ai (Canada), Yottamine Analytics (U.S.), Ersatz Labs, Inc. (U.S.), and Sift Science, Inc. (U.S.) among others
Segments:
The worldwide machine learning as a service market can be classified on the grounds of application, component, end-user, deployment type, organization size, and region.
Based on application, the global machine learning as a service market can be classified into Network analytics, Risk analytics and fraud detection, Predictive maintenance, Marketing, and advertising, Augmented reality, and others.
Based on component, the global machine learning as a service market can be classified into Software tools, Web-based APIs, and Cloud-based APIs.
Based on end-user, the global machine learning as a service market can be classified into Manufacturing, Telecom, BFSI, Government, Healthcare, Transportation, Retail, and others.
Based on the deployment type, global machine learning as a service market can be segmented into Cloud and on-premise.
Based on organization size, global machine learning as a service market can be classified into SMBs and large enterprises.
Based on region, the global machine learning as a service market can be classified into Europe, Asia-Pacific, North America, and the Rest of the World (RoW).
Regional Analysis:
North America led by the U.S. Accounts for the largest share of the global machine learning as a service (MLaaS) market followed by Europe owing to the rapid uptake of new technology, presence of global players and others. However the market is expected to shift towards the developing regions such as Asia Pacific led by Japan, China and India. The Middle East and Africa market is expected to be dominated by Gulf economies of Saudi Arabia, UAE, Kuwait, and Qatar.
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Machine Learning as a Service (MLaaS) Market, 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
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Release ID: 89070743
