💡 Machine Learning from Scratch & scikit-learn 📚

This repository showcases simple, beginner-friendly implementations of:

• 🔵 Linear Regression (for predicting continuous values)
• 🟠 Logistic Regression

Each model is implemented in two ways:

• 🚀 From Scratch using NumPy
• ⚙️ Using scikit-learn for comparison and best practices

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🔧 Setup Instructions

You can run these notebooks using Jupyter Notebook or Google Colab.

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📦 Libraries Used

The following libraries are used in the notebooks to implement the models and preprocess the data:

Library	Description	Documentation Link
numpy	Numerical operations for scratch implementations	NumPy Docs
pandas	Data manipulation and loading	Pandas Docs
matplotlib	Data visualization (graphs and charts)	Matplotlib Docs
scikit-learn	Built-in ML models and data preprocessing tools	Scikit-learn Docs
sklearn.preprocessing	Tools for scaling and encoding data	Sklearn Preprocessing