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_2

2. Big Data, Machine Learning, and Deep Learning Frameworks

Tshepo Chris Nokeri¹  

(1)

Pretoria, South Africa

 

This chapter carefully presents the big data framework used for parallel data processing called Apache Spark. It also covers several machine learning (ML) and deep learning (DL) frameworks useful for building scalable applications. After reading this chapter, you will understand how big data is collected, manipulated, and examined using resilient and fault-tolerant technologies. It discusses the Scikit-Learn, Spark MLlib, and XGBoost frameworks. It also covers ...