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

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 Highlights

In this rapidly changing environment, need for understanding customer behavior is ever increasing. This is driving the machine learning as a service market. The increasing adoption of internet of things (IoT) and big data responsible to drive the Machine learning as a service (MLaaS) market.

Observing the current trend and advancements in technologies the study indicates a sudden hike in Machine Learning as a Service (Mlaas) Market. The Machine learning as a service (MLaaS) market is driven by many factors such as adoption of cloud-based technologies, innovations in automation technologies and others. By adoption of machine learning as a service there is no need to download or install any software. The major challenge of machine learning as a service is lack of historical data, this would be one of the major restraining factor for machine learning as a service (MLaaS) market.

The Machine learning as a service (MLaaS) Market is growing rapidly over 40% of CAGR and is expected to reach at USD ~4630 Billion by the end of forecast period.

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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

Global Machine Learning as a Service (MLaaS) Market - Segmentation

The Machine Learning as a Service Market can be segmented in to 6 key dynamics for the convenience of the report and enhanced understanding;

• Segmentation by Component: Comprises software tools, cloud based API, web based API
• Segmentation by Application: Comprises network analytics, predictive maintenance, augmented reality, marketing and advertising, risk analytics and others
• Segmentation by organization size: Comprises SME and large enterprises.
• Segmentation by deployment: Comprises on-cloud and on-premise
• Segmentation by end-user: Comprises BFSI, manufacturing, healthcare, retail, transportation, telecom and others.
• Segmentation by Regions: Comprises Geographical regions - North America, Europe, Asia Pacific and Rest of the World.

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.

Industry News

January, 2018 – Google LLC, an American Multinational Technology Company launched a new service which aims at businesses by converting machine leaning as a practical tool. This service is called Cloud Auto ML which aims at enterprises lacking expertise in data science by providing machine learning or AI as service.

December, 2017 – Oracle Corporation, an American multinational computer technology corporation, is integrating machine learning across all of its services through the cloud platform. By offering through cloud it makes self-driving, repairing and securing which helps in saving operational costs. This will benefit Oracle by applying AI and machine learning through all of their services which will help customers by lowering cost, reducing risk and to help in making smarter decisions.

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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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