ML-powered athlete injury risk prediction · XGBoost · Gender-specific models · 750k rows · Live dashboard
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Updated
May 17, 2026 - Python
ML-powered athlete injury risk prediction · XGBoost · Gender-specific models · 750k rows · Live dashboard
This project is a web application that allows users to upload a PDF resume downloaded from LinkedIn, extract the text, and generate a professional HTML resume using OpenAI's API. The app is built with Streamlit for the user interface, PyPDF2 for PDF text extraction, and the OpenAI API for generating the HTML format.
AI-powered legal document assistant using NLP and local LLMs with Ollama to summarize, analyze, and simplify legal documents through an interactive Streamlit interface.
I'm a Professional Mistake Avoider, a.k.a. Strategic Advisor.
Production-ready Machine Learning platform for customer churn prediction using Python, Scikit-learn, Streamlit, Docker, and GitHub Actions CI/CD.
This project is a Streamlit application designed to predict the effectiveness of a drug based on its name and the condition it treats. The application uses an XGBoost model to make these predictions. Note: The predictions are based on a simplified model and should be taken with caution. The model uses limited information and random values for many
A serverless pantry manager built with AWS Lambda and Streamlit that tracks item expiry dates and suggests recipes to reduce food waste.
AI-powered Predictive Maintenance System using Random Forest, Industrial IoT sensor data, and Streamlit.
A web app to recommend similar anime based on your input.
Employee Attrition Prediction System using Machine Learning and Streamlit
A Customer Churn Prediction System using machine learning (XGBoost) to classify telecom customers as churn or non-churn. Includes data preprocessing, feature engineering, PCA, and model deployment via Flask, Django, and Streamlit for real-time predictions.
Application for automation and optimization of the distribution of t-shirts at the Juegos Caribe of the Havana University.
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