Machine Learning project that predicts student placement outcomes based on academic performance, employability test scores, and work experience using classification models.
Machine Learning based Student Placement Prediction Web Application using Flask and Random Forest.
A Streamlit-based Machine Learning web application that predicts student placement outcomes using Logistic Regression.
Machine Learning classification project that predicts whether a student will get placed based on academic and skill-related features.
A static placement company landing website built with HTML, CSS, and JavaScript, deployed using GitHub Pages to present placement services and drive engagement.
Streamlit-based ML app for student placement and salary prediction using TensorFlow/Keras.
Minor Machine Learning project on Student Placement Prediction
Beginner friendly Machine Learning project predicting student placement using Logistic Regression.
A web-based Placement Cell Management System that streamlines student recruitment by enabling role-based dashboards, company listings, and application tracking using Firebase.
Machine Learning based student placement readiness assessment platform built using Python, Scikit-Learn and Streamlit.
Machine leaning project for predicting student placement outcomes using python, Scikit-learn,and Flask
A Machine Learning web application that predicts student placement using Gradient Boosting, built with Scikit-learn and Streamlit.
A friendly local-first desktop app for fair student placements using capacity, rules, choices, and road driving times
Student Placement Prediction Model is an end-to-end machine learning project that predicts student placement outcomes based on features like CGPA and IQ. It uses Python (Pandas, Scikit-learn) to process data, train a model, and assess placement probability for each student.
Machine Learning project that predicts student placement probability using CGPA, DSA skills, aptitude, communication, projects, and internship experience.
Predicting student placement based on CGPA and IQ using SVM (Support Vector Machine kernel="rbf").
Student Placement Predictor is a machine learning-based project that predicts whether a student is likely to be placed or not based on academic and skill-related inputs. Built with Scikit-Learn, it uses SVC and Random Forest models and features a Flask-based frontend for real-time prediction.
Machine Learning based Student Placement Prediction Web Application using Flask and Random Forest.
Machine learning project for predicting student placement outcomes using Python and Logistic Regression.
A machine learning model that predicts student campus placements based on academic and personal attributes
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