Lviv JavaClub [Event 402] Tribuo by Ihor Banadiga

The video discusses machine learning and its applications in detecting fraud. The speaker demonstrates a simple example of using a machine learning model to classify data and make predictions. The model is trained on a dataset and then used to predict whether a new transaction is fraudulent or not. The speaker highlights the importance of converting text fields into numerical values and using different models to achieve better accuracy.

The video also touches on the topic of anomaly detection, where the model is used to identify unusual transactions that may be fraudulent. The speaker explains that this approach is often used in payment systems to quickly verify transactions and prevent fraud. The video concludes by highlighting the importance of using machine learning and anomaly detection in financial projects to ensure the security and integrity of transactions.

by Ihor Banadiga Java Software Engineer @ Capgemini Engineering https://www.linkedin.com/in/ihorbanadiga/
Code from the event: https://github.com/lvivJavaClub/Iris-tribuo

Event details: https://www.javaclub.lviv.ua/2026/01/21/Event-402-tribuo.html

Agenda:
0:00:00 – Overview of machine learning and its applications
0:09:50 – Discussion of machine learning in financial projects, including payment systems
0:14:45 – Explanation of how the library can be used for quick verification and fraud detection
0:22:08 – Final thoughts and next steps
0:23:15 – join us #javaclub

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