Machine Learning as a Service (MLaaS) Market 2018 Development Strategy, Key Players Analysis and Forecast Report basics: Definitions, Classifications, Applications and Industry Overview

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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.

Global Machine Learning as a Service (MLaaS) Market   – Overview

Machine learning services is a part of cloud computing services which offers tools of machine learning. The tools include predictive analytics, deep learning, natural language processing and others. The major advantage of these services is that they do not require any kind of installation. They can be utilised directly from the cloud and start deploying tools integrated in it.

Machine learning is driven by algorithms which are capable of recognising patterns in data collection such as text, speech, or images. The cloud is the ideal platform for machine learning due to the storage of huge data and computational performance is high and the deploying cost is low. In Google, machine learning is the foundation for auto data drive systems. The machine learning as a service in Google helped to provide techniques and infrastructure for customers to develop their own interfaces basing Google’s machine platform.

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The increase in volume of data and qualitative techniques for analysing the data, adoption of machine learning across several industries such as retail, healthcare and others are driving the market. Through machine learning data storage became affordable by SME and machine learning helps in making decisions in real time are fuelling the market growth. Lack of historical data which is helpful in providing prediction is hampering the market growth.

Key Players

The prominent players in the Machine Learning as a Service Market are- Google (U.S.), BigML (U.S.), Microsoft (U.S.), IBM (U.S.), Amazon Web Services (U.S.), AT&T (U.S.), (Canada), Yottamine Analytics (U.S.), Ersatz Labs, Inc. (U.S.), and Sift Science, Inc. (U.S.) among others

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.

Global Machine Learning as a Service (MLaaS) Market   – Regional Analysis

The market for machine learning as a service is studied for North America, Europe, Asia Pacific and Rest of the World. North America dominates the market for global machine learning as a service market. U.S. and Canada being the technology hub and place of technology start-ups, many MNC’s are offering machine learning as a service which is the major driving factor in this region. The integration of big data with AI and deployment of technological advancements are fuelling the market in this region. Asia Pacific region is anticipated to show steep growth during the forecast period. The rise in Internet of Things in industries, increase in amount of data and demand for analysis of data and high investments in research and development are driving the market in this region.

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.

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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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