Final Review
Project 1: Fitness Tracker
Description
Began as a simple fitness tracker and evolved into a comprehensive health tracking application.
- Water Tracking: Created an interactive progress bar to monitor water intake.
- Food Tracker: Developed a system for logging meals and calculating a health score based on USDA guidelines. Visualized nutrient intake using pie charts and included machine learning-based suggestions for improvement.
- Expanded Features: Added modules for sleep, exercise, and stress tracking. Integrated a profile system for personalized health recommendations.
- Technologies Used: JavaScript, HTML, CSS, Local Storage, D3.js, SQLite, Python
Links
Project 2: Calorie Burned Calculator
Description
Built a calorie burn prediction tool using regression modeling, first prototyped in Jupyter Notebooks and later deployed via a RESTful API.
- Data Processing: Cleaned and preprocessed data using Pandas; applied one-hot encoding; trained regression models to predict calories burned.
- Backend: Developed a Flask API with endpoints for calorie prediction using user input; stored records in an SQLite database.
- Technologies Used: Python, Jupyter Notebooks, Seaborn, Pandas, Scikit-learn, SQLite, Flask
Links
Project 3: Third Trimester Museum Project
Description
Created a dynamic interface for organizing and exploring exercise card data, merging components from earlier triangle projects.
- Exercise Cards: Enabled sorting and filtering of exercise cards based on likes, intensity, and other user-editable fields.
- Backend: Used SQLite to store, update, and retrieve exercise card data.
- Technologies Used: JavaScript, HTML, CSS, SQLite
Links
Frontend Repository | Backend Repository
Project 4: Slack-Calendar Integration
Description
Designed a productivity tool that connects Slack and Google Calendar to intelligently process messages and create calendar events or reminders.
- Message Processing: Retrieved Slack messages using Slack API; filtered and categorized them using NLP techniques.
- Event Creation: Parsed natural language for date/time info and converted it into calendar events or reminders.
- Use Case: Helps teams turn casual Slack conversations into actionable calendar items.
- Technologies Used: Python, Slack API, Google Calendar API, Flask, SQLite
Links
Live Demo
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Certificates and NFTs (Unique Traits)
Certificates
- Basic Java Proficiency -> AP Test Java
- Basic Spring Java Proficiency -> Spring Java Structure
- Basic SQLite DB Storage + Manipulation (CRUD)
- Basic Frontend Development (HTML/CSS/JS) NFTs
- Basic ngrok proficiency (secure tunneling to localhost)
- Basic Slack API Proficiency
- Slack Bot Proficiency
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Basic fullcalendar.js Proficiency
Homework
- Homework List
- Homework Spreadsheet
- Note: I taught Insertion and Selection
- Average Homework Grade: 0.89
Showcasing Our Work: From HP Expo to N@tM June 2025
HP Expo
At the HP Expo, we demonstrated the core features of Slack-Calendar, focusing on its ability to:
- Automatically parse messages using a consistent template
- Support editing, deleting, and adding events
- UI design (colored assigments generated events)
- Connection to other toolkit features
Loved:
- Liked the connection with other toolkit featues Suggestions:
- Update UI
- Add reminders sidebar feature
N@tM June 2025
Loved:
- The intuitive interface
- rich formatting ability
Suggestions:
- Integrate Gemini AI to help parse more casual or unstructured messages into calendar events.
- Expand functionality to other platforms like Discord or even email clients, making Slack-Calendar more universal.
Past N@tM: Inspiration & Growth
Earlier N@tM events were instrumental in shaping our project. Key takeaways and feedback from these past showings inspired us to:
- Add full CRUD (Create, Read, Update, Delete) functionality for calendar events
- Introduce colored labels for different types of assignments and events
- Support richer parsing, allowing for more expressive and user-friendly formatting
Stats