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.
| 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 |
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
| PlatForm | Link |
|---|---|
| GitHub | krishpansara |
krishpanasara9265@gmail.com |
|
www.linkedin.com/in/krishpansara |