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#Student placement Prediction System
#Overview This project predicts whether a student will be placed based on Academic performances and skills-based features using Machine Learning
#Features -Data Preprocessing -Random Forest model learning -Prediction System -Streamlit Web App -real-time prediction
#Tech Stack -Python -Pandas,NumPy -Scikit-learn -Streamlit
#Input Features -Gender -10th Board and marks -12th Board and marks -Stream -CGPA -Internships -Training -Backlog -Innovative -Communications Skills -Techincal Course
#Output -Placed/Not Placed
#project structure data/ sample.csv notebooks/ eda:ipynb src/ train-model.py predict.py app.py requirements.txt README.md
#How to run 1.Install all dependencies pip install -r requirements.txt 2.train the model cd src/train_model.py 3.Run the streamlit app streamlit run app.py
#Author Nithyashree .L
title:StudentPlacement
colorFrom:blue
colorTo:purple
sdk:streamlit
app_file:app.py