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Pipeline for binary classification algorithm evaluation with nested cross validation and Bayesian hyperparameter tuning with optuna, particularly suited for unbalanced medical datasets.

Python 0.46% Jupyter Notebook 99.54%
classification hepatitis-c-virus hepatitis-prediction machine-learning machine-learning-algorithms medical-data-pipeline optuna pipeline scikit-learn

hepatitisc-ml-prediction-pipeline's Introduction

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💬 About Me:

  • 🔭 Currently completing my thesis for a Master's degree in Data Science.
  • 🤝 Open to collaborating on intriguing Machine Learning or Deep Learning projects.
  • 👨‍💻 All of my projects are available here.

📖 Theory:

  • 🔢 Linear Algebra
  • ∫ Calculus
  • 🔧 Mathematical Optimization
  • 📊 Probability and Statistics
  • 🎯 Supervised Learning
  • 🌌 Unsupervised Learning
  • 🥽 Computer vision

💻 Tech Stack:

Python R NumPy scikit-learn LINUX Streamlit Power Bi Git Pandas PyTorch Keras Matplotlib Plotly MySQLShell Script LaTeX

📈 GitHub Stats:

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Take a look at my projects and let's get in touch 📬

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