Car Price Predictor
ML, WebD
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- A RandomForestRegressor model was trained on the CarDekho dataset from Kaggle post basic feature engineering.
- Hyperparameter tuning was performed for better model accuracy.
- The jupyter notebook containing the model was integrated to the Flask backend using pickle, after which it was deployed as a web-app on Heroku.
Tools: Python, Jinja2 template engine, Flask framework, NumPy, pandas, sklearn, HTML and CSS.
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