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Using data extracted from Kaggle on the top restaurants from 2020, this project utilized Python scripting in Jupyter Notebook to transform and clean the data and finally, load the cleaned data frames into a PostgreSQL database.
This repository contains notebooks in which I have implemented ML Kaggle Exercises for academic and self-learning purposes. In my notebooks, I have implemented some basic processes involved in ML Data Processing like How to take care of Missing Values, Handling Categorical Variables, and operations like mapping, 'Grouping', 'Sorting', 'Renaming …