Filter by discipline to see the models, platforms, and automations behind each engagement.
AI & Machine Learning
Book Recommendation System is a collaborative filtering-based recommendation engine that delivers personalized book suggestions using Nearest Neighbors and Cosine Similarity. Built with Python and Streamlit, it enables users to discover books through an interactive web interface and is deployed on Streamlit Community Cloud.
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AI & Machine Learning
Chizzy Chops Restaurant Chatbot is an AI-powered ordering assistant that automates food ordering, order modifications, and real-time order tracking. Built with FastAPI, Dialogflow, and MySQL, it delivers seamless customer interactions through an intelligent conversational interface integrated into the restaurant's website.
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AI & Machine Learning
GitHub Coach is a multi-agent AI application that analyzes GitHub repositories and intelligently optimizes README files. Built with LangChain, OpenAI GPT, and Streamlit, it provides fact-checked recommendations for project descriptions, documentation, metadata, and structure to improve clarity, discoverability, and developer onboarding.
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AI & Machine Learning
**Short Description:** Built a RAG-powered PDF question-answering assistant that lets users upload PDF documents and ask natural language questions. It uses LangChain, FAISS, and OpenAI GPT to retrieve relevant document content and generate accurate, context-aware answers through a Streamlit web app.
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Data Science
This project analyzes data on OCD patients from 2013–2022 using SQL for data extraction and cleaning, and Power BI for visualization. It explores prevalence trends, demographics, symptom severity, treatment approaches, and patient outcomes. Findings show stable prevalence with a slight increase in diagnoses, higher impact on females and younger individuals, and improved outcomes with combined therapy and medication.
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Data Science
This project analyzes healthcare data from Arcane Falls City to uncover trends, patterns, and key metrics that support better decision-making, resource allocation, and community well-being. Using Microsoft Excel, the study focuses on data analysis, visualization, and interpretation to generate actionable insights.
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