I am a Computer Science Engineering student specializing in AI/ML and Full-Stack Development. I build practical applications that combine machine learning with modern web technologies. My projects include fraud detection, customer churn prediction, recommendation systems, and real-time crowd management. I am currently strengthening my DSA skills and building production-ready full-stack projects.
- AI & Machine Learning: Building predictive pipelines, classification models, and algorithmic solutions.
- Data Science & Analytics: Exploratory data analysis, statistical modeling, feature engineering, and data storytelling.
- Full-Stack Development: Modern, responsive user interfaces integrated with robust Python backend services.
- Intelligent Web Applications: Merging machine learning capabilities seamlessly into web platforms.
- Practical Real-World Software: Engineering clean, maintainable software designed to solve concrete operational problems.
Python • Java • C • JavaScript • SQL
- Core ML & Algorithms: Scikit-learn, XGBoost, Random Forest, Support Vector Machines (SVM), TensorFlow
- Techniques & Methodologies: Feature Engineering, Predictive Analytics, Statistical Analysis, SMOTE, SARIMA
- Data Manipulation & Modeling: Pandas, NumPy, Statsmodels
- Visualization & BI: Matplotlib, Seaborn, Power BI, Microsoft Excel
- Frontend: HTML5, CSS3, JavaScript, React.js, Tailwind CSS
- Backend & APIs: Python, Flask, REST APIs
- Databases: MySQL, SQL
Git • GitHub • VS Code • Jupyter Notebook • Linux
- Tech Stack:
Python,Scikit-learn,Random Forest,SMOTE - Overview: Detects fraudulent transactions using an imbalanced-classification pipeline with SMOTE and Random Forest.
- Tech Stack:
Python,Random Forest,XGBoost,Logistic Regression,Scikit-learn - Overview: Predicts customer churn using an ensemble pipeline combining Random Forest, XGBoost, and Logistic Regression.
- Tech Stack:
Python,Flask,React.js,Random Forest - Overview: Full-stack ML platform for real-time bus tracking, ETA prediction, and crowd management using Flask, React.js, and Random Forest.
- Tech Stack:
Python,SVD,Collaborative Filtering,Scikit-Surprise - Overview: Personalized movie recommendation system using collaborative filtering and Singular Value Decomposition (SVD).
- Tech Stack:
React.js,NASA Open APIs - Overview: Interactive React.js platform using NASA Open APIs to visualize space-weather information.
- Tech Stack:
Python,Flask,SQL - Overview: Full-stack flight booking application with authentication, flight search, booking, cancellation, and SQL-backed data management.
