Machine Learning Algorithms - From Scratch

Overview:

• This project includes manual implementations of fundamental machine learning algorithms alongside their scikit-learn versions for comparison.
• Each algorithm is structured in its own directory with a README, preprocessing steps, and source code.

Included Algorithms:

1. Naive Bayes (Gaussian)
   • Implemented from scratch using NumPy.
   • Compared against scikit-learn’s GaussianNB.
   • Dataset: Breast Cancer Wisconsin.
2. Logistic Regression
   • Manual implementation using batch gradient descent.
   • Compared against scikit-learn’s LogisticRegression.
   • Dataset: Telco Customer Churn.

Notes:

• Each folder includes:
  • Data Preprocessing steps (in a separate file).
  • Manual implementation notebook.
  • scikit-learn implementation notebook.
  • Individual README summarizing problem, data, methods, and results.