According to the latest report by IMARC Group, titled, “Machine Learning as a Service (MLaaS) Market: Global Industry Trends, Share, Size, Growth, Opportunity and Forecast 2023-2028“, Offers a comprehensive analysis of the industry, which comprises insights on the machine learning as a service market growth. The global machine learning as a service (MLaaS) market size reached US$ 5.7 Billion in 2022. Looking forward, IMARC Group expects the market to reach US$ 31.0 Billion by 2028, exhibiting a growth rate (CAGR) of 31.2%during 2023-2028.

Machine learning as a service (MLaaS) refers to a collection of cloud-based platforms that relies on machine learning (ML) tools to deliver solutions. It assists in performing data visualization, application programming interface (APIs), processing natural language, recognizing face and speech, predictive analysis, chatbots, data preprocessing, and deep learning. It enables service providers to host the ML tools for allowing users to access them from numerous devices. It eliminates the requirement of having a specialized and expensive ML infrastructure and makes the ML technology more scalable, approachable, and cost-effective. It automates various tasks and increases the efficiency of several operations that involve manual labor. It helps companies with innovative predictive analysis for numerous use cases. MLaaS also aids businesses in enhancing their customer support services by interacting with targeted clients effectively. It streamlines various ML lifecycle processes, such as data cleaning and preparation, data transformation, and model version control. It allows developers to improve various projects by accessing prebuilt setups and algorithms. It offers data scientists the framework to start with ML without the hassle of software installation and server configuration. It finds applications in small and medium-sized enterprises (SMEs) to reduce expenses by paying only for the hardware.

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Machine Learning as a Service (MLaaS) Market Trends and Drivers:

At present, the rising demand for MLaaS among businesses to automate tasks and reduce infrastructure and server maintenance costs represents one of the primary factors influencing the market positively. Besides this, the increasing cloud computing activities to delegate regular tasks, enhance flexibility and productivity, and strengthen the data security system is propelling the growth of the market. In addition, the rising implementation of advanced data protection strategies in various companies due to the growing number of malicious attacks by hackers to steal confidential information is offering a favorable market outlook. Apart from this, the escalating demand for analytical solutions among large enterprises to get a clear and practical view of business requirements, make better decisions, and increase profits is contributing to the growth of the market. Additionally, the increasing adoption of MLaaS by data engineers to access, analyze, and manage data and create scalable solutions is supporting the growth of the market. Moreover, the rising utilization of MLaaS in the healthcare industry to maintain patient records, conduct better diagnoses, and analyze medical imaging is strengthening the growth of the market. Furthermore, the increasing demand for the internet of things (IoT) in organizations to manage various devices safely and gain beneficial information from caches of data generated by devices is bolstering the growth of the market.

Machine Learning as a Service (MLaaS) Market 2023-2028 Competitive Analysis and Segmentation:

Competitive Landscape:

The competitive landscape of the industry has also been examined along with the profiles of the key players.

  • com Inc.
  • Bigml Inc.
  • Fair Isaac Corporation
  • Google LLC (Alphabet Inc.)
  • ai Inc.
  • Hewlett Packard Enterprise Development LP
  • Iflowsoft LLC
  • International Business Machines Corporation
  • Microsoft Corporation
  • MonkeyLearn
  • Sas Institute Inc.
  • Yottamine Analytics Inc.

The report has segmented the market based on component, organization size, application and end user.

Breakup by Component:

  • Software
  • Services

Breakup by Organization Size:

  • Small and Medium-sized Enterprises
  • Large Enterprises

Breakup by Application:

  • Marketing and Advertising
  • Fraud Detection and Risk Management
  • Predictive Analytics
  • Augmented and Virtual Reality
  • Natural Language Processing
  • Computer Vision
  • Security and Surveillance
  • Others

Breakup by End User:

  • IT and Telecom
  • Automotive
  • Healthcare
  • Aerospace and Defense
  • Retail
  • Government
  • BFSI
  • Other

Breakup by Region:

  • North America
  • Asia-Pacific
  • Europe
  • Latin America
  • Middle East and Africa

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