Data Science Solutions with Python: Fast and Scalable Models Using Keras, PySpark MLlib, H2O, XGBoost, and Scikit-Learn

© The Author(s), under exclusive license to APress Media, LLC, part of Springer Nature 2022

T. C. NokeriData Science Solutions with Pythonhttps://doi.org/10.1007/978-1-4842-7762-1_7

7. Neural Networks with Scikit-Learn, Keras, and H2O

Tshepo Chris Nokeri¹  

(1)

Pretoria, South Africa

 

This chapter executes and assesses nonlinear neural networks to address binary classification using a diverse set of comprehensive Python frameworks (i.e., Scikit-Learn, Keras, and H2O).

Exploring Deep Learning

Deep learning methods transcend machine learning methods. They handle considerable complexity in models and methods by including extensive hidden layers. Machine learning methods typically resemble an input-output system, where an objective function accepts input ...