Placement prediction using machine learning is a technique that analyzes data from past student placements to forecast future job prospects. It uses factors like grades, skills, and experience to estimate the likelihood of a student getting hired. This helps students and institutions better prepare for the job market.

Placement prediction by Artificial Neural Networks. Final Year Bachelor's Project.

Placement Prediction using Machine Learning Models.

Campus Placement Prediction & Management System

This is my final year project. This repository contains everything that you will need for your final project (PPT, Report, Website)

🎯 CareerPredict is your smart career assistant! Just upload your 📄 resume — it auto-fills forms, analyzes your ATS score 🤖, matches you with job descriptions 💼, and gives real-time placement insights 📊 — all in an interactive and engaging way! 🚀✨

A full-stack web application that predicts student placement probability using machine learning. The application consists of a Flask-based REST API backend and a Next.js frontend.

Welcome to the Linear Regression Repository! This repository is dedicated to providing a comprehensive collection of resources and code examples for two types of linear regression: Simple Linear Regression and Multiple Linear Regression.

Enterprise-grade Student Management System built with FastAPI, React, PostgreSQL, and Redis. Features JWT authentication, RBAC, GPA and attendance management, fee automation, AI-powered placement analytics, contextual chatbots, Docker deployment, and CI/CD integration.

Student Performance Portfolio WebApp

A decision-making platform for students to compare internship and job offers with real-world career context

🎯 ML-powered Student Placement Intelligence Platform — predicts placement probability, career fit, skill gap analysis & ATS readiness using Random Forest + Streamlit dashboard.

AI Placement Mentor for College Students using Machine Learning, NLP and Streamlit

This project on placement prediction integrates machine learning with database management using MySQL for user authentication. The project involves data preprocessing, feature engineering, and the implementation of supervised learning techniques to train the model.

Predicting campus placement outcomes using ML - Logistic Regression, Random Forest, KNN comparison

AI-powered placement readiness prediction system using Machine Learning and Streamlit with personalized recommendations and skill analysis.

This app utilizes machine learning to predict student placement outcomes based on CGPA, IQ, and Profile Score, aiding both students and institutions in crucial placement decisions.

AI/ML powered student placement prediction system with React frontend and Flask backend

A machine learning-based system using NLP to automate resume screening and predict placement suitability. It extracts key features and applies KNN for accurate, data-driven recruitment decisions.

Machine Learning system for predicting student placement outcomes using Logistic Regression, Decision Tree, Gradient Boosting and KNN.