Machine learning as-a-service refers to various types of services that offer machine learning abilities as a part of cloud-computing services. MLaaS providers offer various machine learning tools including API, predictive analytics, deep learning, data visualization, natural language processing, etc. MLaaS assists its customers to gain advantage from machine learning without additional cost, risk, and time for creating an in-house internal machine learning team. A number of cloud computing service providers offer machine learning as a service including Amazon, IBM Corporation, and Microsoft Corporation. Moreover, MLaaS is offered on a limited trial basis for a developer to evaluate before committing to a particular platform. The major advantage that MLaaS offers to businesses is that it enables them to get started quickly with machine learning without undergoing tedious software installation processes. Companies can enhance their product capabilities and offerings, enhance regular business operation efficiency, make interaction with consumers easier, and use AI prediction capabilities.

The Global Machine Learning as a Service Market is estimated to account for US$ 98,532.9 Mn in terms of value by the end of 2030.

Market Dynamics

In the 20th century, data is considered the new oil. Due to this many technology companies are heavily investing in data. These data may be in structured and unstructured forms. It has become extremely crucial for these organizations to get a better insight into their data, in order to enhance efficiency and competitiveness. Moreover, many organizations are increasingly adopting machine learning as a service to analyze both structured and unstructured data for future predictions and also use it for further marketing purposes.

Moreover, cloud-based data in continuously growing Cisco system Inc., anticipated in 2015, 65% of data was cloud-based hoverer it is estimated that cloud-based data will reach around 92% by 2020. As more and more companies are preferring cloud computing, it has become easy for them to adopt machine learning services. Moreover, as an ever-increasing number of organizations are leaning toward machine learning, it has gotten simple for them to receive machine learning services. Thus the use of big data and the increasing use of cloud technology are expected to drive the growth of the global machine learning as a service (MLaaS) market during the forecast period.

Key features of the study:

• This report provides an in-depth analysis of the global machine learning as a service (MLaaS) market and provides market size (US$ million) and compound annual growth rate (CAGR %) for the forecast period (2022-2030), considering 2021 as the base year.
• It elucidates potential revenue opportunities across different segments and explains attractive investment proposition matrix for this market
• This study also provides key insights about market drivers, restraints, opportunities, new product launches or approval, regional outlook, and competitive strategy adopted by leading players
• It profiles leading players in the global machine learning as a service (MLaaS) market based on the following parameters – regulatory landscape, company overview, financial performance, product portfolio, geographical presence, distribution strategies, key developments and strategies, and future plans
• Key companies covered in the global machine learning as a service (MLaaS) market are H2O.ai, Google Inc., Predictron Labs Ltd, IBM Corporation, Ersatz Labs Inc., Microsoft Corporation, Yottamine Analytics, Amazon Web Services Inc., FICO, and BigML Inc.
• The key market players are focusing on strategic collaborations to innovate and launch new products to meet the increasing needs and requirements of consumers.
• Insights from this report would allow marketers and management authorities of companies to make informed decision regarding future product launches, technology upgradation, market expansion, and marketing tactics
• The global machine learning as a service (MLaaS) market report caters to various stakeholders in this industry including investors, suppliers, distributors, new entrants, and financial analysts
• Stakeholders would have ease in decision-making through the various strategy matrices used in analyzing the global machine learning as a service (MLaaS) market.

Detailed Segmentation

• Global Machine Learning as a Service (MLaaS)  Market, By Deployment:
  • Public Cloud
  • Private Cloud/Virtual Private Cloud
• Global Machine Learning as a Service (MLaaS)  Market, By End-use Application:
  • Manufacturing
  • Retail
  • Healthcare & Life Sciences
  • Telecom
  • Banking, Financial services and Insurance (BFSI)
  • Others (Energy & Utilities, Government, Education, etc.)
• Global Machine Learning as a Service (MLaaS)  Market, By Region:
  • North America
  • Europe
  • Asia Pacific
  • Latin America
  • Middle East and Africa
• Company Profiles
  • H2O.ai*
    • Company Overview
    • Product Portfolio
    • Financial Performance
    • Key Strategies
    • Recent Developments
  • Google Inc.
  • Predictron Labs Ltd
  • IBM Corporation
  • Ersatz Labs Inc.
  • Microsoft Corporation
  • Yottamine Analytics
  • Amazon Web Services Inc.
  • FICO
  • BigML Inc.

 “*” marked represents similar segmentation in other categories in the respective section.