The Campus Recruitment Placement Prediction Model is a machine learning project aimed at predicting student job placements based on various features provided in the Campus Recruitment dataset from Kaggle. This project employs Support Vector Classification (SVC) algorithm to analyze and predict placement outcomes. The model is designed, implemented, and fine-tuned to accurately predict whether a student will be placed or not. This project demonstrates proficiency in machine learning, data analysis, and model development.
- Utilizes Support Vector Classification for prediction.
- Analyzes various features influencing student job placements.
- Designed to predict placement outcomes accurately.
- Leverages Campus Recruitment dataset from Kaggle.
- Python programming language
- Scikit-learn library for machine learning
- Pandas and NumPy for data manipulation
- Jupyter Notebook for development and visualization
The Campus Recruitment dataset used in this project can be found on Kaggle: Campus Recruitment Dataset.
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Clone the repository:
git clone https://github.com/your-username/campus-recruitment-prediction.git