Machine Learning project that predicts student placement outcomes based on academic performance, employability test scores, and work experience using classification models.

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.

A web-based Placement Cell Management System that streamlines student recruitment by enabling role-based dashboards, company listings, and application tracking using Firebase.

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.

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.

Phase-1 prototype of an AI-Powered Career Intelligence and Employability Analytics Platform using Machine Learning.

Minor Machine Learning project on Student Placement Prediction

Predicting student placement based on CGPA and IQ using SVM (Support Vector Machine kernel="rbf").

Streamlit-based ML app for student placement and salary prediction using TensorFlow/Keras.

Campus Placement Intelligence Dashboard is a Power BI project that analyzes student placement trends, salary insights, specialization performance, gender distribution, and work experience impact. Built using Power BI, Power Query, and DAX, it delivers actionable insights through interactive visualizations and filters.