EAN: 9781484264997

APPLIED DATA SCIENCE USING PYSPARK - RAMCHARAN ...

Discover the capabilities of PySpark and its application in the realm of data science. This
comprehensive guide with hand-picked examples of daily use cases will walk you through the
end-to-end predictive model-building cycle with the latest techniques and tricks of the trade.
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. By the end of this book 
you will have seen the flexibility and advantages of PySpark in data science applications. This
book is recommended to those who want to unleash the power of parallel computing by
simultaneously working with big datasets. What You Will Learn Build an end-to-end predictive
model Implement multiple variable selection techniques Operationalize models Master multiple
algorithms and implementations Who This Book is ForData scientists and machine learning and
deep learning engineers who want to learn and use PySpark for real-time analysis of streaming
data.

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