Machine Learning Portfolio

This repository serves as an overview of my machine learning projects.
I am a Mathematics student at the University of Manchester, with a strong interest in the theoretical foundations of machine learning and data-driven modelling.

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Projects

Kaggle Competitions

• Predicting the Beats-per-Minute of Songs
  Regression task to predict song tempo (BPM) using audio features.
  Model: XGBoost Regressor.
  Evaluation: RMSE on validation split
  Repo: https://github.com/daniil-dev-main/kaggle-song-bpm

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Skills & Tools

• Languages: Python
• Libraries: NumPy, pandas, scikit-learn, XGBoost
• Techniques: Regression, model evaluation, cross-validation, feature engineering
• Tools: Git, GitHub, Jupyter Notebook

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Notes

• Datasets from Kaggle competitions are not included in the repositories and must be downloaded from the respective competition pages.
• Each project repository contains a detailed README with setup instructions and results.

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Contact

GitHub: https://github.com/daniil-dev-main
LinkedIn: https://www.linkedin.com/in/daniil-helman/