Europe Self-supervised Learning Market Size & Forecast, 2028

Europe Self-supervised Learning Market Size, Share & Industry Trends Analysis Report By End-use (BFSI, Advertising & Media, Software Development (IT), Automotive & Transportation, Healthcare), By Technology, By Country and Growth Forecast, 2022 - 2028

Published Date: September-2022 | Number of Pages: 102 | Format: PDF | Report ID: KBV-20577

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Market Report Description

The Europe Self-supervised Learning Market would witness market growth of 32.8% CAGR during the forecast period (2022-2028).

Machineries can foresee through natural evolution & the results of their actions by using self-supervised learning, much like how newborns can learn an incredible amount of information in their first few weeks or months of life by noticing and being curious. Self-supervised learning has the capacity to scale learning to the levels required by novel use cases, such as but not limited to use cases in image recognition, autonomous driving, robotics, and medicine.

Target labeling is done by hand in supervised learning, and a programmer is required to oversee the training procedure. In unsupervised learning, the algorithm must sift through a vast amount of data and look for patterns using techniques like clustering and matrix decomposition. Increased automation is possible with the unsupervised approach, but prediction accuracy may suffer.

The G-Cloud initiative of the British government aims to make it simpler for public sector organizations in the UK to acquire standard information technology services that utilize cloud computing. Public sector organizations can purchase services through the G-Cloud without having to go through a full procurement process that involves tenders or competition due to a set of framework agreements with suppliers. Online marketplace "Digital Marketplace" enables public sector organizations to look for services that adhere to G-Cloud principles.

The Germany market dominated the Europe Self-supervised Learning Market by Country in 2021, and would continue to be a dominant market till 2028; thereby, achieving a market value of $3,445.5 million by 2028. The UK market is anticipated to grow at a CAGR of 31.7% during (2022 - 2028). Additionally, The France market would exhibit a CAGR of 33.8% during (2022 - 2028).

Based on End-use, the market is segmented into BFSI, Advertising & Media, Software Development (IT), Automotive & Transportation, Healthcare, and Others. Based on Technology, the market is segmented into Natural Language Processing (NLP), Computer Vision, and Speech Processing. Based on countries, the market is segmented into Germany, UK, France, Russia, Spain, Italy, and Rest of Europe.

Free Valuable Insights: The Global Self-supervised Learning Market will Hit $51.7 Billion by 2028, at a CAGR of 33.3%

The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include Baidu, Inc., Apple, Inc., Tesla, Inc., IBM Corporation, Microsoft Corporation, Amazon Web Services, Inc. (, Inc.), Meta Platforms, Inc., SAS Institute, Inc., The MathWorks, Inc., and DataRobot, Inc.

Scope of the Study

Market Segments Covered in the Report:

By End-use

  • BFSI
  • Advertising & Media
  • Software Development (IT)
  • Automotive & Transportation
  • Healthcare
  • Others

By Technology

  • Natural Language Processing (NLP)
  • Computer Vision
  • Speech Processing

By Country

  • Germany
  • UK
  • France
  • Russia
  • Spain
  • Italy
  • Rest of Europe

Key Market Players

List of Companies Profiled in the Report:

  • Baidu, Inc.
  • Apple, Inc.
  • Tesla, Inc.
  • IBM Corporation
  • Microsoft Corporation
  • Amazon Web Services, Inc. (, Inc.)
  • Meta Platforms, Inc.
  • SAS Institute, Inc.
  • The MathWorks, Inc.
  • DataRobot, Inc.

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Related Reports:

Global Self-supervised Learning Market Report 2022-2028

North America Self-supervised Learning Market Report 2022-2028

Asia Pacific Self-supervised Learning Market Report 2022-2028

LAMEA Self-supervised Learning Market Report 2022-2028

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