Name		Name	Last commit message	Last commit date
.gitignore		.gitignore
README.md		README.md
app.py		app.py
eda.py		eda.py
feature_importance.py		feature_importance.py
label_encoder.pkl		label_encoder.pkl
machine_learning.py		machine_learning.py
placement_model.pkl		placement_model.pkl
processing.py		processing.py
requirements.txt		requirements.txt
student_dataset_v2.csv		student_dataset_v2.csv
student_dataset_v3.csv		student_dataset_v3.csv

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Placement Readiness Digital Twin

An AI-powered student placement prediction system built using Machine Learning and Streamlit.

Features

Placement Readiness Prediction
Company Fit Analysis
Readiness Score
Confidence Analysis
Interactive Streamlit Dashboard

Technologies Used

Python
Pandas
Scikit-Learn
Random Forest
Streamlit
Joblib

Dataset Features

CGPA
Aptitude Score
Coding Score
DSA Score
Communication Score
Projects
Internships
Backlogs

Run Locally

pip install -r requirements.txt
streamlit run app.py

About

Placement Readiness Digital Twin is a machine learning project that predicts a student’s placement suitability using academic and aptitude features. It uses Python and a Streamlit app to give quick, interactive insights.

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