"Student_Placement_Prediction_Web_App" that focuses on a web application for predicting student placements using machine learning algorithms like Random Forest Classification , Logistic Regression and using Streamlite give an web interference

This project uses machine learning algorithms (Random Forest Classifier and Decision Tree) to predict student placement likelihood based on age, gender, CGPA, internships, and backlogs. It provides actionable employability insights, aiding career planning. A user-friendly Flask web app will be deployed on Render for broad accessibility.

A Student Placement Prediction Webapp using Logistic Regression that can predict your placement so that you can check your progress further.