README.md

Machine learning Using Pyspark

This is a helpful notebook which contains:

• Creating a Spark application.
• Using Spark sql for manipulating the dataframe
• Using data processing steps (feature encoding, scaling, selection ...)
• Training and Testing ml-models

In This notebook I tested almost machine learning algorithms:

• DECISION TREE
• Deep Learning Multilayer Perceptron
• NAIVE BAYES
• LOGISTIC REGRESSION
• One-vs-Rest
• RANDOM FOREST

Note that this notebook was made in google colab so you don't need to install any package just run cells in google colab + I used keystroke data and Touch data

Helpful notebook, Yeah!