Applied Data Science Using PySpark is divided unto six sections which walk you through the book. In secti..."> Applied Data Science Using PySpark is divided unto six sections which walk you through the book. In secti..."/>
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Applied Data Science Using PySpark

Applied Data Science Using PySpark is divided unto six sections which walk you through the book.
In section 1, you start with the basics of PySpark focusing on data manipulation. We make you comfortable with the language and then build upon it to introduce you to the mathematical functions available off the shelf.
In section 2, you will dive into the art of variable selection where we demonstrate various selection techniques available in PySpark. In section 3, we take you on a journey through machine learning algorithms, implementations, and fine-tuning techniques. We will also talk about different validation metrics and how to use them for picking the best models.
Sections 4 and 5 go through machine. learning pipelines and various methods available to operationalize the model and serve it through Docker/an API. In the final section, you will cover reusable objects for easy experimentation and learn some tricks that can help you optimize your programs and machine learning pipelines.

Availability
#
Information Technology 006.2/KAK/IT0759
IT0759
Available
Detail Information
Series Title
-
Call Number
006.2/KAK/IT0759
Publisher
Jersey : APRESS.,
Collation
-
Language
English
ISBN/ISSN
978-1-4842-8373-8
Classification
NONE
Content Type
-
Media Type
-
Carrier Type
-
Edition
First Edition
Subject(s)
IT
Data Science
Specific Detail Info
-
Statement of Responsibility
Other version/related

No other version available

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