VICTOR    MENESTREL
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suspicious pathway analysis
artificial intelligence
Navigating the realm of gaming, I embarked on a mission to address the issue of rampant cheating on Minecraft, a disheartening deterrent for virtuous players. Centralizing my proficiency across diverse domains, I engineered a holistic approach to this predicament.

Foundational to this endeavor was the creation of 2D trajectory depictions, meticulously capturing distinct patterns of both cheating and honest players. Employing a convolutional neural network driven by Python, Keras, and TensorFlow, a sophisticated training process was orchestrated, highlighting the mastery of artificial intelligence techniques.
Strategically bridging the gap between Java, Python, Keras, and TensorFlow, I established a dual-server architecture. Python, Keras, and TensorFlow orchestrated backend analysis on a separate server, while a Java plugin directly interfaced with the Minecraft environment, channeling data to the analysis server through an intermediary SQL database.

Real-world scenarios substantiated the efficacy of this innovation, with the technology seamlessly countering cheating software. This multifaceted project highlights my journey of learning in harmonizing technology, programming, and data manipulation.
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