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.)
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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.
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.
Market Research Future (MRFR), in its recently published research report, asserts that the global machine learning as a service (MLaaS) market is booming and expected to grow exponentially by 2022, registering a striking CAGR throughout the forecast period 2020-2022. MRFR also predicts that the global machine learning as a service (MLaaS) market might reach approximately USD 4630 million, registering a stellar 40% CAGR throughout the period.
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.
Drivers and Restraints:
The increasing adoption of machine learning by the enterprises for facilitating quick decision making is likely to fuel the growth of machine learning as a service (MLaaS) market over the review period. Automation is one of the major factors driving the growth of machine learning as a service (MLaaS) market. The expanding market presence of automation has restricted human intervention, thus, paving the way for the growth of the MLaaS market in the foreseeable future. Data has become the backbone of organizations. The increasing demand for predictive analysis across the end-user industry verticals, along with the shift towards data science, has released myriad opportunities for the expansion of machine learning as a service (MLaaS) market. In addition to this, the developments introduced in the machine learning tools such as face recognition, APIs, data visualization, natural language processing, predictive analytics, and deep learning are expected to fuel the expansion of the global machine learning as a service (MLaaS) market during the assessment period.
Furthermore, the incorporation of cloud computing in machine learning has fueled the growth of machine learning as a service (MLaaS) market. The market is at a promising stage and has been assumed to display an entry of startups that are in a better position to support rapid technological developments. The growing demand for machine learning as a service (MlaaS) has been prognosticated to remain highly lucrative over the next couple of years.
Segmental Analysis:
The global market for machine learning as a service (MLaaS) has been analyzed on the basis of component, application, deployment, and end-user.
Based on the Component, the global machine learning as a service (MLaaS) market has been segmented into Cloud APIs, Software tools, Web-based APIs
ON the basis of the Application, the machine learning as a service (MLaaS) market has been segmented into Predictive maintenance, Network analytics, Augmented reality
Based on the deployment, the global market for machine learning as a service (MLaaS) has been bifurcated into on-cloud and on-premise.
ON the basis of the end-user, the machine learning as a service (MLaaS) market has been segmented into BFSI, healthcare, manufacturing, transportation, retail, government, transportation, telecom, government, 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.
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.
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