- 🔭 Current Focus: Working on Crime Data Analysis and Prediction to uncover patterns and forecast criminal activities.
- 🌱 Learning Journey: Exploring Neural Networks, NLP, and Computer Vision to tackle diverse data science challenges.
- 👯 Collaborative Spirit: Open to collaborations on Machine Learning and Data Science Projects.
- 💬 Ask Me About: Python, Data Science, Machine Learning, and how I make code both functional and fun.
- 📫 Contact: Reach me at sahupoulomi@gmail.com.
- ⚡ Fun Fact: My code thinks it's funny, and sometimes, I agree!
- Description: Leveraging machine learning to analyze and predict crime patterns for enhanced community safety.
- Technologies: Python, Scikit-learn, Pandas, Seaborn.
- Impact: Improved predictive accuracy for high-crime zones by 20%.
- Description: Predicting employee attrition to aid companies in retaining top talent.
- Technologies: Random Forest, Logistic Regression, SMOTE.
- Impact: Delivered actionable insights that reduced attrition rates by 15%.
- Description: Identified customers likely to purchase personal loans to enhance campaign targeting.
- Technologies: Logistic Regression, Random Forest, Gradient Boosting.
- Impact: Increased campaign success rates by 18%.
Thank you for exploring my GitHub profile! Feel free to reach out for collaborations or discussions. Let's create impactful solutions together.