This presentation from STRONGER discussed practical tips for building predictive risk models using Python and open-source libraries. Professor Huwyler explored how these models can detect unusual activity and threats in real-time, providing valuable insights to enhance cybersecurity measures. The session offered practical tips and recommendations, complete with code examples that you can implement immediately. He'll discuss various use cases to illustrate how these predictive risk models can be applied in real-world scenarios. Professor Huwyler demonstrated how to build these models with Python and published this code on a free-to-use platform, ensuring accessibility for all attendees from this session.
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