How to Use Pyspark For Your Machine Learning Project

How to Use Pyspark For Your Machine Learning Project

In this tutorial, we will present how to use Pyspark to do exactly what you are used to see in a Kaggle notebook (cleaning, EDA, feature engineering and building models).

Pyspark is a Python API that supports Apache Spark, a distributed framework made for handling big data analysis. It’s an amazing framework to use when you are working with huge datasets, and it’s becoming a must-have skill for any data scientist.

In this tutorial, I will present how to use Pyspark to do exactly what you are used to see in a Kaggle notebook (cleaning, EDA, feature engineering and building models).

I used a database containing information about customers for a telecom company. The objective is to predict which clients will leave (Churn) in the upcoming three months. The CSV file with the data contains more than 800,000 rows and 8 features, as well as a binary Churn variable.

machine-learning apache-spark big-data pyspark python

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