My Projects
Traditional Chinese Medicine - Internet of Tongues
- Collaborated with an external client, developed an application to predict traditional Chinese medicine syndromes using tongue images.
- Our approach leverages computer vision to explore syndrome classification pathways, aiming to refine a model that accurately links visual tongue features (shape, color, coating, size, etc.) to specific syndromic predictions.
Preventing Decision Paralysis
- Currently focused on identifying and validating the best resources and sources of information to enhance our solutions for decision paralysis in critical areas.
- Pharmaceutical Drug Discovery: This would be a system to assist individuals with chronic illnesses, such as Parkinson's disease, by providing comprehensive information on available medications, their overall effects, and potential side effects.
- Disaster Management: Creating a dashboard for first responders, offering live updates on weather data to facilitate informed decision-making during emergencies.
The Rise and Fall of Somali Pirates
- Designed an interactive dashboard using Python, Streamlit, and Plotly to analyze the rise and fall of Somali piracy.
- Performed geospatial and temporal analysis to uncover trends, regional hotspots, and economic impacts.
- Delivered actionable insights on counter-piracy strategies through engaging visualizations for stakeholders.
Fruit Ripeness Detection
- Developed a Python-based machine learning system using a CNN to identify and segregate ripe and unripe fruits.
- The CNN model demonstrates the project's technological innovation and its seamless integration into the agricultural sector.
Movie Recommendation System
- Created a movie recommendation web app using the Dash framework.
- Utilized Python for data cleaning, formatting, and implementing a Collaborative Filtering algorithm to predict user preferences from historical data.
Sentiment Analysis of Tweets
- A web app that can predict the sentiments of a tweet (positive, negative, or neutral) in real time.
- Utilized the Twitter API to gather real-time tweet data, applying NLP techniques through Python and Django to accurately classify positive, negative, or neutral tweets.