🧠 Machine Learning From Scratch in Python

Welcome to the Machine Learning From Scratch repository — a collection of core ML algorithms implemented in pure Python, without relying on libraries like scikit-learn or TensorFlow.

This project is built for students, developers, and enthusiasts who want to understand the inner workings of machine learning algorithms by building them from the ground up.

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🚀 What's Inside?

Algorithm	Category	Status
✅ Linear Regression	Regression	✔️ Completed
✅ Multiple LinearReg.	Regression	✔️ Completed
✅ Logistic Regression	Classification	✔️ Completed
✅ Polynomial Regression	Regression	✔️ Completed
✅ Decision Tree	Classification	✔️ Completed
✅ Gradient descent	Classification	✔️ Completed
✅ Random Forest	Ensemble	✔️ Completed
✅ K-Nearest Neighbors	Classification	✔️ Completed
✅ Naive Bayes	Classification	✔️ Completed
🔜 Support Vector Machine	Classification	✔️ Completed

And many more....

🧠 Why Build From Scratch?

Building models from scratch helps you:

✅ Understand the math and intuition behind ML
✅ Learn how models optimize and generalize
✅ Develop better debugging and ML skills
✅ Prepare for ML interviews and research work

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✅ What to Replace

PlatForm	Link
GitHub	krishpansara
Email	krishpanasara9265@gmail.com
LinkedIn	www.linkedin.com/in/krishpansara

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