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Data science encompasses a wide range of areas, topics, and sub-domains such as Big Data, Machine & Deep learning (ETL, TensorFlow, Keras), Data Mining/Visualization (EDA), BI, Predictive Analytics, Statistical Analytics, etc.
In this jupyter notebook file, fictional data of football players was used to perform big data analytics in python. It involves using librarires such as pandas and matplotlib.
This repository is a comprehensive collection of notebooks that covers various data science projects in detail. Each project is designed to provide a clear understanding of the data science pipeline, from data acquisition to model deployment.
This is my final project for PSTAT 135, Big Data Analytics, using PySpark to conduct county-wide voter turnout regression analysis by demographic. This project was done in collaboration with Tyler Kim and Erasmo Rivas. The GCP storage bucket linked below contains the full project, while the Jupyter notebook and exported PDF are included here.