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  • Machine Learning with PySpark: With Natural Language Processing and Recommender Systems

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Pramod Singh
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Machine Learning with PySpark: With Natural Language Processing and Recommender Systems 1st ed. Edition, Kindle Edition

by Pramod Singh (Author) Format: Kindle Edition
4.0 out of 5 stars (16)
Build machine learning models, natural language processing applications, and recommender systems with PySpark to solve various business challenges. This book starts with the fundamentals of Spark and its evolution and then covers the entire spectrum of traditional machine learning algorithms along with natural language processing and recommender systems using PySpark. 
Machine Learning with PySpark shows you how to build supervised machine learning models such as linear regression, logistic regression, decision trees, and random forest. You’ll also see unsupervised machine learning models such as K-means and hierarchical clustering. A major portion of the book focuses on feature engineering to create useful features with PySpark to train the machine learning models. The natural language processing section covers text processing, text mining, and embedding for classification. 
After reading thisbook, you will understand how to use PySpark’s machine learning library to build and train various machine learning models. Additionally you’ll become comfortable with related PySpark components, such as data ingestion, data processing, and data analysis, that you can use to develop data-driven intelligent applications.
What You Will Learn
  • Build a spectrum of supervised and unsupervised machine learning algorithms
  • Implement machine learning algorithms with Spark MLlib libraries
  • Develop a recommender system with Spark MLlib libraries
  • Handle issues related to feature engineering, class balance, bias and variance, and cross validation for building an optimal fit model

Who This Book Is For 
Data science and machine learning professionals. 
Read more
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  1. ISBN-13
    978-1484241318
  2. Edition
    1st ed.
  3. Publisher
    Apress
  4. Accessibility
    Learn more
  5. Publication date
    December 14, 2018
  6. Language
    English
  7. File size
    9.9 MB
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Product details

  • ASIN ‏ : ‎ B07LDMMMFP
  • Publisher ‏ : ‎ Apress
  • Accessibility ‏ : ‎ Learn more
  • Publication date ‏ : ‎ December 14, 2018
  • Edition ‏ : ‎ 1st ed.
  • Language ‏ : ‎ English
  • File size ‏ : ‎ 9.9 MB
  • Screen Reader ‏ : ‎ Supported
  • Enhanced typesetting ‏ : ‎ Enabled
  • X-Ray ‏ : ‎ Not Enabled
  • Word Wise ‏ : ‎ Not Enabled
  • Print length ‏ : ‎ 262 pages
  • ISBN-13 ‏ : ‎ 978-1484241318
  • Page Flip ‏ : ‎ Enabled
  • Best Sellers Rank: #7,120 in Computers & Technology Industry
  • Customer Reviews:
    4.0 out of 5 stars (16)

About the author

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Pramod Singh

Pramod Singh

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Pramod Singh is currently a Manager , Data Science at Bain & Company. He has over 11 years of rich experience in Data Science field working with multiple product and service based organisations.He has been part of numerous ML & AI large scale projects.He has published 4 books on Large Scale Data Processing & Machine Learning. He is also a regular speaker at major AI conferences such as O’Reilly AI & Strata conference.

Customer reviews

4 out of 5 stars
16 global ratings

Top reviews from the United States

  • Vikranth Reddy Kasireddy
    3.0 out of 5 stars Very high level.
    Reviewed in the United States on December 29, 2021
    Format: KindleVerified Purchase
    Doesn’t involve the main concepts behind spark context configuration. Not worth the price tag for the content. It’s a book to quickly read through if money is not an issue.
    Helpful
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  • RLKurtz
    2.0 out of 5 stars Reasonably clearly written, but with significant problems.
    Reviewed in the United States on July 19, 2020
    Format: Paperback
    The good first, the text in the book is clear and you should be able to follow along.

    However, while the author explains how to do machine learning on the test data he doesn't elaborate on how that would be implemented in the day-to-day operation. Essentially, you'll be able to calculate 'something', but you are left in the dark about what do with it.

    Now, for the code.
    Variables change name halfway through the chapter, some parts of the code appears to be missing (e.g. section on developing the confusion matrix), the cluster chapter straight up doesn't work because someone in their infinite wisdom decided to cut the required functionality and the supporting file for the last part the natural language processing chapter is missing completely. There is a github for the book where the .csv file has been requested, but it's yet to be uploaded. In conclusion, you'll get real intimate with the forumdwellers trying sort out all the problems...
    2 people found this helpful
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Top reviews from other countries

  • Abdoul
    5.0 out of 5 stars great book
    Reviewed in Canada on May 16, 2019
    Format: PaperbackVerified Purchase
    Good for someone trying to learn pyspark and sparkML. it is detailled and focus on ML
    Report
  • fallout
    5.0 out of 5 stars Good book to start with spark machine learning
    Reviewed in India on September 10, 2019
    Format: PaperbackVerified Purchase
    Very easy language used to understand the basics
    Report
  • Mello
    3.0 out of 5 stars Not really a book
    Reviewed in Germany on October 20, 2023
    Format: PaperbackVerified Purchase
    This books looks like a API documentation
    Report
  • Enrique
    2.0 out of 5 stars Too Basic
    Reviewed in Germany on October 11, 2022
    Format: PaperbackVerified Purchase
    too basic, at that level better almost a Yt tutorial.
    Report
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