Machine Learning as a Service (MLaaS) Market 2018 Global Leaders: Amazon Web Services, Yottamine Analytics, Ersatz Labs, Sift Science, Microsoft, IBM, BigML, Google

Market Research Future published a research report on “Machine Learning as a Service (MLaaS) Market Research Report- Forecast 2022” – Market Analysis, Scope, Stake, Progress, Trends and Forecast to 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 Machine Learning as a Service (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.

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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.

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

Machine learning as a service (MLaaS) Market Segmentation

The Machine learning as a service (MLaaS) market has been segmented on the basis of component, application, organization size, deployment and end-user. Looking through the End-user segment it’s been observed that healthcare segment would dominate the Machine learning as a service (MLaaS) market. It has been observed that there is a need for handling the structured and unstructured data generated by the electronic health record (EHR). The study reveals that considering the deployment segment, the cloud based Machine learning as a service (MLaaS) shows a significant growth due to the increasing adoption of cloud technologies and is expected to show a sudden hike by the forecast period.

Market Research Analysis:

Regional analysis for Machine learning as a service (MLaaS) market is studied in different geographic regions as Americas, Europe, Asia-Pacific and Rest of world. It has been observed that North America region would account for larger share in Machine learning as a service (MLaaS) market. The study indicates that North America region has high technological developments and high adoption of internet of things (IoT) this has resulted in the growth of Machine learning as a service (MLaaS) market in North America region. The study reveals that Asia-Pacific region is expected to show a significant growth in Machine learning as a service (MLaaS) market by the forecast period. Asia-Pacific countries like China, India and Korea are investing in internet of things.

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Intended Audience:

• Machine learning as a service (MLaaS) vendors
• Resellers and distributors
• Technology investors
• System Integrators
• Government Organizations
• Research/Consultancy firms
• Network solution providers
• Independent software vendors
• Managed Security Service Providers (MSSPs)

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