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Essential PySpark for Scalable Data Analytics

You're reading from   Essential PySpark for Scalable Data Analytics A beginner's guide to harnessing the power and ease of PySpark 3

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Product type Paperback
Published in Oct 2021
Publisher Packt
ISBN-13 9781800568877
Length 322 pages
Edition 1st Edition
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Author (1):
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Sreeram Nudurupati Sreeram Nudurupati
Author Profile Icon Sreeram Nudurupati
Sreeram Nudurupati
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Table of Contents (19) Chapters Close

Preface 1. Section 1: Data Engineering
2. Chapter 1: Distributed Computing Primer FREE CHAPTER 3. Chapter 2: Data Ingestion 4. Chapter 3: Data Cleansing and Integration 5. Chapter 4: Real-Time Data Analytics 6. Section 2: Data Science
7. Chapter 5: Scalable Machine Learning with PySpark 8. Chapter 6: Feature Engineering – Extraction, Transformation, and Selection 9. Chapter 7: Supervised Machine Learning 10. Chapter 8: Unsupervised Machine Learning 11. Chapter 9: Machine Learning Life Cycle Management 12. Chapter 10: Scaling Out Single-Node Machine Learning Using PySpark 13. Section 3: Data Analysis
14. Chapter 11: Data Visualization with PySpark 15. Chapter 12: Spark SQL Primer 16. Chapter 13: Integrating External Tools with Spark SQL 17. Chapter 14: The Data Lakehouse 18. Other Books You May Enjoy

Classification

Classification is another type of supervised learning technique, where the task is to categorize a given dataset into different classes. Machine learning classifiers learn a mapping function from input parameters called Features that go to a discreet output parameter called Label. Here, the learning function tries to predict whether the label belongs to one of several known classes. The following diagram depicts the concept of classification:

Figure 7.2 – Logistic regression

In the preceding diagram, a logistic regression algorithm is learning a mapping function that divides the data points in a two-dimensional space into two distinct classes. The learning algorithm learns the coefficients of a Sigmoid function, which classifies a set of input parameters into one of two possible classes. This type of classification can be split into two distinct classes. This is known as binary classification or binomial classification.

Logistic regression...

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