Machine Learning Algorithms – Learning & Practice

This repository contains simple implementations of common Machine Learning algorithms using Jupyter Notebooks.

⚠️ Note:
This project is created purely for learning and practice purposes.
The code in this repository is adapted and borrowed from the following article:

🔗 Source:
15 Most Commonly Used Machine Learning Algorithms in Python

All credit for the original implementations and explanations goes to the author.

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📌 Algorithms Covered

The repository includes example notebooks for the following algorithms:

• Linear Regression
• Logistic Regression
• Decision Tree
• Random Forest
• Support Vector Machines(SVM)
• KNN

Each notebook demonstrates:

• Basic concept and usage
• Model training and prediction
• Simple evaluation and visualization

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🧠 Purpose of This Repository

This repository is meant to:

• Practice core ML algorithms
• Strengthen understanding of ML fundamentals
• Serve as a personal reference for revision and interviews

It is not intended for production use or as an original research contribution.

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🛠️ Tech Stack

• Python
• Jupyter Notebook
• NumPy
• Pandas
• Matplotlib
• Scikit-learn