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

Placement Prediction using Machine Learning Models.

Campus Placement Prediction & Management System

Placement prediction website(Flask web application) predicts the chance of getting placed on-campus based on various parameters like CGPA, backlogs, internships, etc. This website uses a Machine Learning model trained using Random Forest Classification technique. The machine learning model achieved 94% precision and 88% accuracy.

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.

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.

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.

Student Performance Portfolio WebApp

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.

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