Implementation of Logistic Regression for UCI dataset

Requirements

The core libraries used across projects include but are not limited to:

  • Python 3.8+
  • NumPy
  • Pandas
  • Scikit-learn
  • TensorFlow / PyTorch
  • Matplotlib / Seaborn
  • Jupyter Notebook

The goal is to showcase a practical approach to building, training, and evaluating a logistic regression model using Python and popular machine learning libraries like Scikit-learn.