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.

PLACEMATE is a helping tool for engineering students who wants to predict their placement possibility and evaluate themselves. It can also generate professional resume for a student in PDF format

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

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.

The project aims to analyze past placement data, uncover factors affecting success, and develop a machine learning model to predict future placement outcomes. Through this, we aim to gain insights and build a reliable model for accurately forecasting candidate placements.

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.

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.

Campus Placement Prediction & Management System

Tensorflow Sequential Model to predict the placement probability percentage of a student

Placement Prediction using Machine Learning Models.

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