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real-world-data

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A python implementation of “Self-Supervised Learning of Spatial Acoustic Representation with Cross-Channel Signal Reconstruction and Multi-Channel Conformer” [TASLP 2024]

  • Updated Oct 11, 2024
  • Python

Predicts which telecom customers are likely to churn with 95% accuracy using real-world data features from usage, billing, and support data. Implements Sturges-based binning, one-hot encoding, stratified 80/20 train-test split, and a two-level ensemble pipeline with soft voting. Achieves 94.60% accuracy, 0.8968 AUC, 0.8675 precision, 0.7423 recall.

  • Updated Jun 16, 2025
  • Python

This is the coding and solution for my MSc Computer Science Thesis (2023) that uses Garmin FIT files to visualise athletes data for their own training development

  • Updated Dec 12, 2023
  • Python
Visual-Healthcare-Insights-Python-EDA-Power-BI-Dashboards

🩺 Healthcare Data Integration, Analysis & Visualization project using Python, Jupyter Notebook, and Power BI. Integrates multi-sheet Excel data, performs data cleaning, feature engineering, exploratory analysis, and delivers interactive healthcare dashboards.

  • Updated May 13, 2025
  • Jupyter Notebook

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