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A portfolio of hands-on ML projects covering regression, classification, and ensemble methods — built with Python and scikit-learn.
| # | Project | Technique | Description |
|---|---|---|---|
| 1 | Students Score | Simple Linear Regression | Predicts exam scores from study hours |
| 2 | Weather Temperature Prediction | Multiple Linear Regression | Predicts daily temperature from sunlight hours and humidity |
| 3 | Patient Health Risk Prediction | Ridge / Lasso Regression | Predicts health risk scores from vitals and lifestyle data |
| 4 | Social Network Ads | Logistic Regression | Predicts purchase behavior from user demographics |
| 5 | Titanic Survival Prediction | Binary Classification | Predicts passenger survival on the Titanic dataset |
| 6 | Dry Bean Classification | Multiclass Classification | Classifies 7 dry bean varieties using geometric shape features |
| 7 | Weather Classification | Multiclass Classification | Classifies weather types from meteorological features |
| 8 | Decision Pet Adoption | Decision Tree | Predicts pet adoption outcomes using a Decision Tree classifier |
| 9 | Cancer Prediction | Random Forest / Ensemble | Compares Decision Tree (86%) vs Random Forest (91%) vs Tuned RF (94%) |
Python · NumPy · Pandas · Scikit-learn · Matplotlib · Seaborn · Jupyter Notebook
- GitHub: @RawatXd
- LinkedIn: abhishek-rawat-5s5
- Email: abhishekrawat.du.or.26@gmail.com ⭐ Star this repo if you find it useful!