Data Science Portfolio

This repository highlights my applied data science and machine learning projects, showcasing experience relevant to Senior Data Scientist roles in industry.
The projects demonstrate predictive modeling, recommender systems, and explainable AI — with a focus on building actionable insights from complex data.

---

🔍 Projects Included

1. Recommender Systems

• Collaborative Filtering (user-based and item-based).
• Matrix Factorization with gradient descent.
• Implementation in Python using Pandas, NumPy, and Scikit-learn.

2. Predictive Modeling

• Regression and classification tasks on real-world datasets.
• Feature engineering and model selection.
• Performance evaluation using cross-validation and metrics such as RMSE, F1-score, and ROC AUC.

3. Explainable AI

• Model interpretation using LIME and SHAP.
• Demonstrates transparency and accountability in AI models.

4. Time Series Forecasting

• Forecasting with ARIMA, LSTM, or Prophet.
• Applications in financial risk and demand prediction.

---

🛠 Tools & Technologies

• Languages: Python, R, SQL
• Libraries: Scikit-learn, TensorFlow, PyTorch, Pandas, NumPy, Matplotlib, Seaborn
• Explainability: LIME, SHAP
• Deployment: Docker (where applicable)