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The project aims to create a comprehensive web app using Streamlit, Anaconda, Jupyter Notebook, and Spyder, predicting Diabetes, Heart Disease, and Parkinson's. It uses ML models on diverse health data for personalized predictions, empowering users to manage health proactively.
The "Customer Prediction Analysis Streamlit" GitHub repository contains all the files related to a project that analyzes customer data using a dummy dataset. The repository includes Jupyter notebooks for data preprocessing, exploratory data analysis, and model training.
Welcome to the Mushroom Prediction Model repository! This project aims to identify poisonous and edible mushrooms using machine learning techniques. Developed in a Jupyter Notebook and deployed with Streamlit, the model offers an interactive and user-friendly interface for mushroom classification.
This project repository hosts notebook, manifests and guides to deploy dog breed classification Machine Learning Web Application on Google Kubernetes Engine (GKE) Autopilot.