© Ramcharan Kakarla, Sundar Krishnan and Sridhar Alla 2021
R. Kakarla et al.Applied Data Science Using PySparkhttps://doi.org/10.1007/978-1-4842-6500-0_7

7. Unsupervised Learning and Recommendation Algorithms

Ramcharan Kakarla1  , Sundar Krishnan1 and Sridhar Alla2
(1)
Philadelphia, PA, USA
(2)
New Jersey, NJ, USA
 

This chapter will explore popular techniques used in the industry to handle unlabeled data. You will discover how you can implement them using PySpark. You will also be introduced to the basics of segmentation and recommendation algorithms and the data preparation involved therein. By end of this chapter, you will have an appreciation for unsupervised techniques and their use in day-to-day data science activities.

We will cover the ...

Get Applied Data Science Using PySpark: Learn the End-to-End Predictive Model-Building Cycle now with the O’Reilly learning platform.

O’Reilly members experience live online training, plus books, videos, and digital content from nearly 200 publishers.