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noise-analysis

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A lightweight research-oriented project analyzing how noise, missing values, and corrupted features affect machine learning model reliability. Includes synthetic data generation, multi-model training, and noise-impact evaluation with visualization. Designed as a teaching/learning artifact for data quality, robustness, and ML reliability concepts.

  • Updated Nov 28, 2025
  • Python

Quantum Noise Analysis for Quantum Addition: Part of the Quantum Computing Mentorship Program Screening Task. This repository explores the effects of noise on quantum computations, implements quantum addition using the Draper adder algorithm, and demonstrates techniques to mitigate noise impact on quantum circuits.

  • Updated Oct 27, 2024
  • Jupyter Notebook

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