This portfolio showcases cutting-edge machine learning research across multiple domains:
- Bangla Sentiment Analysis using LSTM, GRU and RNN architectures
- Custom word embeddings for low-resource language processing
- State-of-the-art results with limited linguistic resources
- Diabetic Retinopathy Classification using ensemble methods
- Multi-feature extraction pipeline (SIFT, Sobel, Color, Gray)
- Medical image processing with high accuracy (92%)
- Weather Pattern Analysis using deep neural networks
- Multi-variable regression with custom architecture
- Precise temperature prediction (RMSE: 1.2°C)
- Bangla Sign Language Classification
- Real-time processing capabilities
- Enhanced accessibility solutions
- Languages: Python 3.8+
- Deep Learning: PyTorch, TensorFlow, Keras
- Computer Vision: OpenCV, scikit-image
- Data Science: NumPy, Pandas, scikit-learn
- NLP: BNLP Toolkit
- Development: Git, Jupyter, VS Code
- Computing: GPU Acceleration, Google Colab
- Developed novel approaches for Bangla language processing
- Achieved 92% accuracy in medical image classification
- Created efficient weather prediction models
- Advanced sign language recognition technology
| Project | Metrics | Impact |
|---|---|---|
| Sentiment Analysis | Accuracy: 85-90%, F1: 0.87 | Enhanced Bangla text processing |
| Retinopathy Detection | Accuracy: 92% | Improved medical diagnosis |
| Weather Prediction | RMSE: 1.2°C | Precise temperature forecasting |
| Sign Language | Real-time processing | Better accessibility |
Each project includes:
- Detailed documentation
- Implementation code
- Results analysis
- Future development roadmap
from models.sentiment import SentimentAnalysis
# Initialize the analyzer with desired architecture
analyzer = SentimentAnalysis(architecture='LSTM')
# Process text
text = "আপনার টেক্সট এখানে লিখুন" # Write your text here
sentiment = analyzer.predict(text)- Healthcare: Supporting early disease detection
- Language: Advancing Bangla NLP capabilities
- Environment: Improving weather predictions
- Accessibility: Enhancing communication tools
- Modular Design: Easy to understand and extend
- GPU Optimization: Efficient model training
- Comprehensive Documentation: Detailed explanations
- Research Focus: Novel approaches to complex problems
- Detailed project portfolio
- Implementation details
- Performance analysis
For research collaboration or employment opportunities, please reach out!
This research portfolio is available under the MIT License.