Machine learning as a service market is growing at an exponential rate as it satiates the need for advanced services. The global machine learning as a service market is expecting a growth by an impressive 40% CAGR in the forecast period (2016-2022) with which it can scale valuation of USD 4630 million in the same forecast period, asserts Market Research Future (MRFR) in a comprehensive study. The report further includes drivers that are backed by some excellent features, which is driving the machine learning as a service market at a rapid rate and is expected to chart its course positively towards the future.
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Drivers & Trends
The range of services that machine learning as a service offers are generally connected to machine learning tools as part of cloud computing services. These services hence include data visualization, APIs, face recognition, natural language processing, predictive analytics and deep learning. The prime advantage of machine learning as a service offers the customers in getting started on a quick note with machine learning without downloading and installing any software at their end.
The drivers of the market include the increased volume of data and diverse that handles it qualitatively. These factors are drastically contributing to the growth of Machine Learning as a Service (MLaaS) market since the past years, and are expected to proceed in the same way during the assessment period. The report further includes drivers such as innovations in automation technologies and increasing adoption of cloud-based systems is also boosting the growth of the market globally. Backed by such excellent features, the market is to experience more traction than before and would earn higher valuation during the assessment period.
Apart from the availability of data storage at a cheaper rate as well as high adoption of Internet of Things (IoT) is also motivating the Machine Learning as a Service (MLaaS) market to flourish in the coming years. On the flip side, the study indicates that a lack of historical data is posing as one of the foremost restraining factors in the course of growth of machine learning as a service (MLaaS) market.
Machine learning as a Service (MLaaS) market, as per the study has been segmented based on component, application, organization size, deployment and end-user.
By the mode of component, the global machine learning as a service (MLaaS) market is segmented into software tools, cloud APIs, web-based APIs.
By the mode of application, machine learning as a service market has been segmented into network analytics, predictive maintenance, augmented reality.
By the mode of deployment, the global market has been segmented into on-cloud and on-premise.
By the mode of end-user, MLaaS Market has been segmented into manufacturing, healthcare, BFSI, transportation, government, retail, transportation, government, telecom, and others.
The global machine learning as a service market, according to the region, has covered the main regions of Asia Pacific, North America, Europe and the Rest of the World (RoW).
Among these, North America is now expected to scale new heights and lead the market throughout the forecast period. In this region, the U.S. and Canada are noted as highly contributing places to the most significantly towards the growth of machine learning as a service market.
After North America, Europe is also in line to expect significant growth with the support of the rapid developments that had been introduced in machine learning. On the other hand, Asia Pacific is also anticipated to exhibit positive growth in the coming years. The growth can be thus ascribed to the thriving country-level markets of China, Japan, South Korea, and India, among others. With this, highly investments that are being done through thorough R&D in these countries are also a reason for market growth in the Asia Pacific.
The well-known players in the machine learning as a service (MLaaS) Market are listed as 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.) and many others.
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