π MS in Data Science
π University of Colorado Boulder
π‘ Passionate about building Machine Learning, Data Engineering, and Analytics solutions that solve real-world problems.
Predictive ML system analyzing GDP, happiness index, and suicide rates to assess risk factors with real-time prediction planning.
| Model | Accuracy | Highlights |
|---|---|---|
| KNN | 97% | Top performer |
| XGBoost | 95% | Feature importance |
| Random Forest | 94% | Ensemble boost |
π View Project β
Analyzed anxiety levels using lifestyle, physiological, and behavioral data to predict severity scores.
Key Insight: Caffeine + poor sleep + high stress = anxiety spike π
| Technique | Purpose |
|---|---|
| PCA + K-Means | Clustering anxiety profiles |
| Apriori | Association rule mining |
| Naive Bayes / SVM | Severity classification |
| XGBoost | Final prediction model |
π View Project β
Let's collaborate and build something impactful! π

