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18 May 2026


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Machine learning algorithms for anomaly detection Greek.pptx

This PowerPoint presentation provides an introduction to machine learning algorithms for anomaly detection, covering various techniques such as clustering, autoencoders, and one-class support vector machines. It details the steps involved in applying machine learning, including data collection, processing, and model evaluation, and addresses challenges like overfitting and hyperparameter tuning, with examples and references included. AI generated

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Project information

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Acronym

CyberSecPro


Title

Collaborative, Multi-modal and Agile Professional Cybersecurity Training Program for A Skilled Workforce In the European Digital Single Market and Industries


Description

CyberSecPro promotes a conceptual disruptive approach with regards to existing approaches to training solutions. The project contributes to the broader need for cybersecurity marketing skills and technical/practical capabilities.
CyberSecPro aims to upskill and develop a workforce capable of overcoming the increasing security challenges that will burden innovation and excellence. This overarching goal can be achieved with the methodology adopted in the CyberSecPro project.
Further, the project utilises the processes developed within many EU Cybersecurity pilot projects and adppts relevant EU innovation and development work:

CyberSecPro will drive the HEIs to further enhance their cooperation with the private sector, in order to become the main suppliers of the necessary market-oriented cybersecurity skills and working-life practices required in the digital transformation, via providing hands-on trainings.


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Materials

747 files | 8.38 GB


Last updated

05/2026


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964 file downloads | 10.02 GB