Applied Data Science Using Pyspark: Learn The End-to-end Predictive Model-building Cycle

December 18, 2020|
Applied Data Science Using Pyspark: Learn The End-to-end Predictive Model-building Cycle by Ramcharan Kakarla
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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 PySparkis 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 For

Data scientists and machine learning and deep learning engineers who want to learn and use PySpark for real-time analysis of streaming data.
Ramcharan Kakarla  is currently lead data scientist at Comcast residing in Philadelphia. He is a passionate data science and artificial intelligence advocate with five+ years of experience. He holds a master''s degree from Oklahoma State University with specialization in data mining. Prior to OSU, he received his bachelor''s in el...
Title:Applied Data Science Using Pyspark: Learn The End-to-end Predictive Model-building Cycle
Product dimensions:410 pages, 10 X 7.01 X 0 in
Shipping dimensions:410 pages, 10 X 7.01 X 0 in
Published:December 18, 2020
Appropriate for ages:All ages
ISBN - 13:9781484264997

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