https://github.com/ad1tyaraj/student-placement-model
Predicting student placement is a crucial step for universities and recruiters in understanding and enhancing the employability of students. This machine learning model uses CGPA and resume scores as input features to predict the likelihood of a student being placed.
https://github.com/ad1tyaraj/student-placement-model
django flask machine-learning ml python
Last synced: 3 months ago
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Predicting student placement is a crucial step for universities and recruiters in understanding and enhancing the employability of students. This machine learning model uses CGPA and resume scores as input features to predict the likelihood of a student being placed.
- Host: GitHub
- URL: https://github.com/ad1tyaraj/student-placement-model
- Owner: Ad1tyaRaj
- Created: 2025-01-11T18:19:53.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-01-11T18:36:21.000Z (over 1 year ago)
- Last Synced: 2025-10-23T21:52:51.729Z (8 months ago)
- Topics: django, flask, machine-learning, ml, python
- Language: HTML
- Homepage: https://ad1tyaraj.github.io/Portfolio/
- Size: 5.86 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
**Project Title**
**Predicting Student Placement: CGPA and Resume Score**
**Overview**
This project aims to create a machine learning model that can predict whether a student will be placed or not based on their CGPA and resume score.
**Table of Contents**
- [Project Description](https://github.com/Ad1tyaRaj/Student-placement-model#project-description)
- [Technologies Used](https://github.com/Ad1tyaRaj/Student-placement-model#technologies-used)
- [Dataset](https://github.com/Ad1tyaRaj/Student-placement-model#dataset)
- [Installation Guide](https://github.com/Ad1tyaRaj/Student-placement-model#installation-guide)
- [Usage](https://github.com/Ad1tyaRaj/Student-placement-model#usage)
**Project Description**
Predicting student placement is a crucial step for universities and recruiters in understanding and enhancing the employability of students. This machine learning model uses CGPA and resume scores as input features to predict the likelihood of a student being placed.
**Features**
- **Input Features**: CGPA, Resume Score
- **Output**: Placement status (Placed/Not Placed)
**Technologies Used**
- Python
- Scikit-learn
- Pandas
- Numpy
- Matplotlib
- Seaborn
**Dataset**
The dataset contains information on students' CGPA and resume scores along with their placement status. It is sourced from university placement data and preprocessed for the model's use.
**Dataset Structure**
- **CGPA**: Cumulative Grade Point Average of the student
- **Resume Score**: A score calculated based on resume attributes such as skills, projects, etc.
- **Placement Status**: Binary target variable (Placed/Not Placed)
These models are trained to predict the placement status based on CGPA and resume score.
**Installation Guide**
1. Clone the repository:
```
git clone https://github.com/YourUsername/StudentPlacementPrediction.git
```
2. Navigate to the project directory:
```
cd StudentPlacementPrediction
```
3. Install required dependencies:
```
pip install -r requirements.txt
```
**Usage**
1. Prepare your data with CGPA and resume score.
2. Load the trained model:
```
import pickle
import numpy as np
pipe = pickle.load(open('pipe.pkl','rb'))
```
3. Use the model to predict placement:
`input_data = [[cgpa, resume_score]] # Replace with your data
prediction = model.predict(input_data)
print(prediction)`