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The Medical Recommendation System predicts diseases based on user-input symptoms and provides recommendations for medications, diets, precautions, and workouts. Built using machine learning models …
End-to-end Olist E-commerce Data Engineering pipeline using Azure services. Includes data ingestion, transformation, storage, and analytics with ADLS, Data Factory, Databricks, MongoDB, and Synapse.
A Gemini LLM-powered project that translates natural language queries into SQL commands, retrieving data from an SQLite database through a user-friendly Streamlit interface.
This project leverages U-Net for lung region segmentation and CNN for cancer classification using CT scan images. It aims to enhance lung cancer detection accuracy through deep learning techniques.…
Gemini LLM Applications showcase text-based Q&A, image analysis, and chat history capabilities using Google Gemini API. Built with Streamlit, these apps provide intelligent and interactive solution…
The Diamond Price Prediction project leverages machine learning to predict diamond prices based on key attributes. It features a Flask web app for real-time, accurate price estimation.