Machine Learning as a Service Market Size To Expand at a Notable CAGR Of 40% During 2016 - 2022

Pune, India, February,2019/MRFR Press Release/- Market Research Future has published a half-cooked research report on the Global Machine Learning as a Service Market.

Market Synopsis

According to Market Research Future (MRFR)’s latest report, the global machine learning as a service (MLaaS) market is poised to strike a stellar CAGR of 40% during the forecast period 2016 to 2022. The valuation of the market has been estimated to reach USD 4630 Mn by the end of 2023. The growing adoption of machine learning by the enterprises for facilitating quick decision making is expected to drive the growth of the market.

Automation is one of the key factors driving the growth of the machine learning as a service (MLaaS) market. The increasing market presence of automation has restricted human intervention, thus, paving the way for the growth of the MLaaS market in the upcoming years.

Data has become the backbone of organizations. The growing demand for predictive analysis across the end-user industry verticals coupled with the shift towards data science has unleashed myriad opportunities for the expansion of the machine learning as a service (MLaaS) market. In addition, the developments introduced in the machine learning tools such as APIs, face recognition, data visualization, predictive analytics, natural language processing, and deep learning are expected to propel the expansion of the market.

The integration of cloud computing in machine learning has initiated the growth of the machine learning as a service (MLaaS) market. The market is at a nascent stage and has been presumed to exhibit an influx of startups who are at a better position to sustain rapid technological developments. The machine learning as a service (MLaaS) market has been prognosticated to remain highly lucrative over the next couple of years.

Market Segmentation:

By Component, the global machine learning as a service (MLaaS) market has been segmented into Software tools, Cloud APIs, Web-based APIs

By Application, the machine learning as a service (MLaaS) market has been segmented into Network analytics, Predictive maintenance, Augmented reality

By deployment, the global machine learning as a service (MLaaS) market has been segmented into on-cloud and on-premise.

By end-user, the machine learning as a service (MLaaS) market has been segmented into manufacturing, healthcare, BFSI, transportation, government, retail, Transportation, government, telecom, and others.

Regional Insights:

The global machine learning as a service (MLaaS) market, by region, has been segmented into Asia pacific, North America, Europe and the Rest of the World (RoW). North America has been expected to scale new heights and dominate the market through the forecast period. The U.S. and Canada are poised to contribute most significantly towards the growth of the machine learning as a service (MLaaS) market in the region. Europe, too, is expected to witness significant growth owing to the rapid developments introduced in machine learning. Asia Pacific is anticipated to exhibit positive growth over the next couple of years. The growth can be ascribed to the thriving country-level markets of China, Japan, South Korea, and India among others.

Competitive Dashboard:

Some of the important players profiled in this MRFR report are BigML (U.S.), Microsoft (U.S.), Ersatz Labs, Inc. (U.S.), Google (U.S.), IBM (U.S.), AT&T (U.S.), Fuzzy.ai (Canada), Amazon Web Services (U.S.), Yottamine Analytics (U.S.), and Sift Science, Inc. (U.S.).

Industry News:

In February 2019, Calix, Inc., a global provider of the cloud and software platforms, has added machine learning capabilities to its behavioral analytics-based churn prediction services.

In February 2019, IBM, a tech-giant, has offered its Watson data crunching technology to corporate customers who have deployed IBM’s cloud computing service.

In February 2019, Affinity, a San Francisco startup, has announced the launch of its “relationship intelligence” platform that leverages machine learning for managing relationships.