A professional portfolio dashboard built with Streamlit showcasing Machine Learning and Data Science projects.
Advanced NLP pipeline using DistilBERT transformer for sentiment analysis with aspect extraction. Identifies specific aspects (Food, Service, Price) from customer reviews.
Tech Stack: Transformers, Hugging Face, PyTorch, Streamlit
View Project →
Quantitative finance tool for analyzing stock market trends and real-time sentiment analysis. Provides data-driven insights for investment decisions.
Tech Stack: Pandas, NumPy, Plotly, Streamlit
View Project →
High-performance image recognition engine using ResNet50 deep learning. Identifies 1000+ object categories with 92%+ accuracy.
Tech Stack: TensorFlow, Keras, ResNet50, Streamlit
View Project →
Medical diagnostic interface using Random Forest classification to predict health risks from clinical metrics.
Tech Stack: Scikit-Learn, Streamlit, Joblib
View Project →
Frontend & Deployment:
- Streamlit
- Custom CSS & HTML
- Responsive Design
Machine Learning & Data Science:
- TensorFlow / Keras
- PyTorch
- Scikit-Learn
- Hugging Face Transformers
- Pandas / NumPy
- Plotly
Deployment:
- Streamlit Cloud
- GitHub
Machine Learning: Deep Learning, NLP, Computer Vision, Classification, Time Series
Data Science: Data Analysis, Data Visualization, Statistical Modeling
Programming: Python, API Integration, SQL
Tools: Jupyter, Git, GitHub, Streamlit, Scikit-Learn
"A good developer knows the math behind the code."
This portfolio reflects my commitment to understanding both how to build applications and why they work:
- Mathematical foundations of algorithms
- Deep learning architecture understanding
- Data-driven decision making
- Production-grade code quality
portfolio-hub/
├── app.py # Main Streamlit application
├── requirements.txt # Dependencies
└── README.md # This file
# Install dependencies
pip install -r requirements.txt
# Run the app
streamlit run app.pyThe app will open at http://localhost:8501
- 💼 Upwork: Hire me on Upwork
- 🔗 LinkedIn: Connect on LinkedIn
- 📂 GitHub: View GitHub Profile
✅ Built 4 production-grade ML applications
✅ Implemented advanced NLP pipelines with transformers
✅ Achieved 98% accuracy in medical predictions
✅ Developed image recognition with 1000+ categories
✅ Real-time data processing and analysis
✅ Clean, documented, deployable code
- ✨ Added PyTorch support
- 🚀 Launched Cancer Detection Model
- 📊 Improved portfolio UI/UX
- 🔄 Updated all project links
Made with ❤️ by Ali Faraz | April 2026