Project using machine learning to predict depression using health care data from the CDC NHANES website. A companion dashboard for users to explore the data in this project was created using Streamlit. Written with python using jupyter notebook for the main project flow/analysis and visual studio code for writing custom functions and creating th…

A scoring model and the interactive dashboard for Fraud Detection

A comprehensive MNIST digit recognition project with a Streamlit dashboard, neural network model, and Jupyter notebook. Includes all necessary files for training, testing, and deploying the model.

This project uses Natural Language Processing (NLP) and Machine Learning techniques to analyze user reviews of top-selling games on the Steam platform. The goal is to detect bug-related reviews using keyword filtering, assess user sentiment (positive, neutral, negative), and group similar games using clustering methods.

This project uses Natural Language Processing (NLP) and Machine Learning techniques to analyze user reviews of top-selling games on the Steam platform. The goal is to detect bug-related reviews using keyword filtering, assess user sentiment (positive, neutral, negative), and group similar games using clustering methods.

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.

This is a simple use of streamlit to share analysis of a bike share dataset. On this repository includes analysis notebook file, requirements dependencies, dirty and cleaned dataset,and python file that use to create streamlit app.