Machine learning as a service is the group of several tools needed for communication such as predictive analysis, face recognition, natural language processing, deep learning, data visualization and APIs. This service helps in receiving faster responses and solutions about machine learning and also without installing any kind of software. This augments the performance efficiency and hence saves the cost.
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Key Driving Factors: Impact of Developing Countries
The key factor which is projected to drive the market growth is the influence of developing countries. The developing countries have high potential for the machine learning as a service market, due to a low adoption base and establishing infrastructure. Further, the requirement for cost-effective predictive solutions among end-use industries in developing countries is also fueling the demand for machine learning as a service.
The key competitors operating in the market are Google Inc., Hewlett Packard Enterprise, Microsoft Corporation, FICO, Predictron Labs Ltd., SAS Institute Inc., Yottamine Analytics, Amazon Web Services, BigML Inc., and IBM Corporation.
Driver: Growing Application Areas to Fuel the Market
Growth in automation and advancement in technology are anticipated to boost the adoption rate of machine learning as a service in various applications. Machine learning technology has propelled the emergence of predictive analytics which experiences quicker growth in consumption and has become a prominent aspect of all business operations and processes. Predictive analytics is used in several online activities which eventually drives the market growth.
By End User
Based on the end user, the retail & e-commerce segment is estimated to grow at a faster CAGR during the forecast period as the retail industry is rapidly changing into digital space. In addition, the retail and e-commerce sectors are adopting machine learning as-a-service to enhance their customer experience and enhance operational efficiency.
The Machine Learning as a Service (MLaaS) Market report has been categorized as below
By Organization Size
By End User
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Published Date : June-2021