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Learn Pyspark - by  Pramod Singh (Paperback) - 1 of 1

Learn Pyspark - by Pramod Singh (Paperback)

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Highlights

  • Learn PySparkChapter 1: Introduction to PySparkChapter 2: Data ProcessingChapter 3: Spark Structured StreamingChapter 4: AirflowChapter 5: Machine Learning Library (MLlib)Chapter 6: Supervised Machine LearningChapter 7: Unsupervised Machine LearningChapter 8: Deep Learning Using PySpark
  • About the Author: Pramod Singh is currently a Manager (Data Science) at Publicis Sapient and working as data science lead for a project with Mercedes Benz.
  • 210 Pages
  • Computers + Internet,

Description



Book Synopsis




Learn PySpark
Chapter 1: Introduction to PySpark
Chapter 2: Data Processing
Chapter 3: Spark Structured Streaming
Chapter 4: Airflow
Chapter 5: Machine Learning Library (MLlib)
Chapter 6: Supervised Machine Learning
Chapter 7: Unsupervised Machine Learning
Chapter 8: Deep Learning Using PySpark



From the Back Cover



Leverage machine and deep learning models to build applications on real-time data using PySpark. This book is perfect for those who want to learn to use this language to perform exploratory data analysis and solve an array of business challenges.
You'll start by reviewing PySpark fundamentals, such as Spark's core architecture, and see how to use PySpark for big data processing like data ingestion, cleaning, and transformations techniques. This is followed by building workflows for analyzing streaming data using PySpark and a comparison of various streaming platforms.
You'll then see how to schedule different spark jobs using Airflow with PySpark and book examine tuning machine and deep learning models for real-time predictions. This book concludes with a discussion on graph frames and performing network analysis using graph algorithms in PySpark. All the code presented in the book will be available in Python scripts on Github.



About the Author



Pramod Singh is currently a Manager (Data Science) at Publicis Sapient and working as data science lead for a project with Mercedes Benz. He has spent the last nine years working on multiple Data projects at SapientRazorfish, Infosys & Tally and has used traditional to advanced machine learning and deep learning techniques in multiple projects using R, Python, Spark and Tensorflow. Pramod has also been a regular speaker at major conferences in India and abroad and is currently authoring a couple of books on Deep Learning and AI techniques. He regularly conducts Data Science meetups at SapientRazorfish and presents webinars on Machine Learning and Artificial Intelligence. He lives in Bangalore with his wife and 2-year-old son. In his spare time, he enjoys coding, reading and watching football.
Dimensions (Overall): 9.21 Inches (H) x 6.14 Inches (W) x .48 Inches (D)
Weight: .72 Pounds
Suggested Age: 22 Years and Up
Number of Pages: 210
Genre: Computers + Internet
Publisher: Apress
Theme: Python
Format: Paperback
Author: Pramod Singh
Language: English
Street Date: September 7, 2019
TCIN: 84704891
UPC: 9781484249604
Item Number (DPCI): 247-28-5381
Origin: Made in the USA or Imported
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Shipping details

Estimated ship dimensions: 0.48 inches length x 6.14 inches width x 9.21 inches height
Estimated ship weight: 0.72 pounds
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Q: Where can the code examples be found?

submitted by AI Shopping Assistant - 10 days ago
  • A: All code examples from the book are available in Python scripts on GitHub.

    submitted byAI Shopping Assistant - 10 days ago
    Ai generated

Q: Who is the author of this book?

submitted by AI Shopping Assistant - 10 days ago
  • A: The author is Pramod Singh, a Data Science Manager at Publicis Sapient.

    submitted byAI Shopping Assistant - 10 days ago
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Q: Is the book suitable for beginners?

submitted by AI Shopping Assistant - 10 days ago
  • A: Yes, it starts with PySpark fundamentals, making it accessible for beginners in data science.

    submitted byAI Shopping Assistant - 10 days ago
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Q: What is the primary focus of the book?

submitted by AI Shopping Assistant - 10 days ago
  • A: The book focuses on leveraging PySpark for big data processing and machine learning applications.

    submitted byAI Shopping Assistant - 10 days ago
    Ai generated

Q: What topics are covered in the book?

submitted by AI Shopping Assistant - 10 days ago
  • A: The book covers PySpark fundamentals, data processing, machine learning, deep learning, and real-time data analysis.

    submitted byAI Shopping Assistant - 10 days ago
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