Projects
Selected technical projects demonstrating applied ML skills. For research projects, see the Research page. Click any row to view details.
Deep LearningBangladeshi Flower Image Classification
- Deep learning–powered web app for classifying 13 types of Bangladeshi flowers.
- Transfer learning with MobileNetV2 (fine-tuned last 50 layers) on a custom curated dataset.
- Advanced data augmentation pipeline (rotation, shift, shear, zoom, flip) to improve model robustness.
- Achieved 99.87% validation accuracy with real-time classification and confidence scores via a Streamlit app.
Tools / Technology: Python, TensorFlow/Keras, Streamlit, OpenCV, PIL, NumPy, Pandas
NLPSentiment Analysis on Social Media Data
- Analyze social media posts to classify sentiment (positive, negative, neutral) using transformer models.
- Implemented custom tokenization and feature-extraction pipelines for multilingual text processing.
- Deployed an interactive dashboard for real-time sentiment analysis with visualization of trends.
Tools / Technology: Python, Hugging Face Transformers, spaCy, NLTK, BERT, RoBERTa
Machine LearningAnomaly Detection in Network Traffic
- Detect anomalies in network traffic for cybersecurity, performance monitoring, and compliance.
- Isolation Forest (unsupervised ML) with temporal feature engineering for pattern recognition.
- Developed an automated alert system with configurable thresholds and notification mechanisms.
Tools / Technology: Python, Scikit-learn, Pandas, Streamlit, Plotly