Distributed Machine Learning with PySpark: Migrating Effortlessly from Pandas and Scikit-Learn

© The Author(s), under exclusive license to APress Media, LLC, part of Springer Nature 2023

A. TestasDistributed Machine Learning with PySparkhttps://doi.org/10.1007/978-1-4842-9751-3_12

12. Neural Network Classification with Pandas, Scikit-Learn, and PySpark

Abdelaziz Testas¹  

(1)

Fremont, CA, USA

 

In this chapter, we explore the world of Multilayer Perceptron (MLP) classifiers, a powerful approach to supervised machine learning. MLPs have several advantages, making them versatile for a wide range of tasks, from regression to classification spanning across various domains such as image recognition, natural language processing, and speech recognition, to name a few.

One key advantage is that MLPs can approximate any continuous function given enough ...