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behavioral-modeling

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A complete machine-learning system that predicts AI assistant user satisfaction using behavioral signals such as device, usage category, time features, session metrics, and model metadata. Includes full ML pipeline, SHAP explainability, evaluation suite, and an interactive Streamlit analytics dashboard.

  • Updated Jul 4, 2026
  • Python

This repository contains Verilog HDL implementations of Half Adders, Full Adders, and 4-bit Adders, designed at three different abstraction levels: Gate Level, Dataflow Level, and Behavioral Level. These designs are fundamental to digital electronics, and this project showcases the versatility of Verilog in modeling and simulating digital circuits.

  • Updated Aug 24, 2024
  • Verilog

SUBIT‑64 is a universal semantic operating system built on six binary axes, an eight‑layer semantic stack, and a 64‑node hypercubic topology. It provides a minimal, interpretable, and dynamic framework for modeling meaning, cognition, behavior, and system transitions across domains.

  • Updated Feb 5, 2026
  • JavaScript

A sophisticated Python framework for modeling and simulating psychological personality systems. This project enables dynamic personality evolution through event simulation, allowing for realistic modeling of how life experiences shape personality traits and psychological attributes.

  • Updated Sep 3, 2026
  • Python

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