Machine-Learning-Portfolio

This repository contains my end-to-end machine learning work:

• Algorithms implemented from scratch and using sklearn
• Clear mathematical intuition behind models
• Proper evaluation, feature engineering, and pipelines
• Real-world projects with clean structure

Tech Stack

• Python, NumPy, Pandas, Matplotlib, Seaborn
• scikit-learn
• Jupyter Notebook

Learning Path

• ML theory & implementation via 100 Days of ML (CampusX)
• Math intuition: Linear Algebra, Calculus, Probability & Statistics