🩺 Diabetes Prediction Application with Python & Streamlit | Machine Learning Project
In this video, we dive into building an interactive application using Python and Streamlit to predict diabetes based on health metrics. From loading and analyzing data to visualizing insights and tuning the model, we cover every step to create a comprehensive health analysis tool.
In this video:
Setup: Learn how to set up a Streamlit app to analyze diabetes data.
Interactive Input: Use sliders to input health metrics and see real-time predictions.
Model Tuning: Adjust model hyper parameters to improve prediction accuracy.
Visualizations: Visualize health data with scatter plots and understand diabetes risk factors.
Exporting Results: Export a PDF report summarizing the user's health metrics and prediction.
🔗 GitHub Repository: https://github.com/404reese/ML-projec...
📌 Resources:
Streamlit Documentation: https://docs.streamlit.io/deploy/stre...
Pandas Documentation: https://pandas.pydata.org/docs/user_g...
Matplotlib Documentation: https://matplotlib.org/stable/users/e...
Seaborn Documentation: https://seaborn.pydata.org/tutorial/f...
🔗 Connect with me:
Github: https://github.com/404reese
Website: https://riddhesh.vercel.app/
Thank you for watching!