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|z 9781119561934
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|z 9781119561958
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|a 9781119561934
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|a UAMI
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|a Bowles, Michael,
|e author.
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|a Machine Learning with Spark and Python, 2nd Edition /
|c Bowles, Michael.
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|a 2nd edition.
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|b Wiley,
|c 2019.
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|a 1 online resource (368 pages)
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|a text
|b txt
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|a Machine Learning with Spark and Python Essential Techniques for Predictive Analytics, Second Edition simplifies ML for practical uses by focusing on two key algorithms. This new second edition improves with the addition of Spark-a ML framework from the Apache foundation. By implementing Spark, machine learning students can easily process much large data sets and call the spark algorithms using ordinary Python code. Machine Learning with Spark and Python focuses on two algorithm families (linear methods and ensemble methods) that effectively predict outcomes. This type of problem covers many use cases such as what ad to place on a web page, predicting prices in securities markets, or detecting credit card fraud. The focus on two families gives enough room for full descriptions of the mechanisms at work in the algorithms. Then the code examples serve to illustrate the workings of the machinery with specific hackable code.
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|f Copyright © 2019 by John Wiley & Sons
|g 2019
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|a Made available through: Safari, an O'Reilly Media Company.
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|a Online resource; Title from title page (viewed November 5, 2019)
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|a O'Reilly
|b O'Reilly Online Learning: Academic/Public Library Edition
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|a Spark (Electronic resource : Apache Software Foundation)
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|a Spark (Electronic resource : Apache Software Foundation)
|2 fast
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|a Machine learning.
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650 |
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|a Python (Computer program language)
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650 |
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|a Apprentissage automatique.
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650 |
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6 |
|a Python (Langage de programmation)
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650 |
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7 |
|a Python (Computer program language)
|2 fast
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|a Machine learning
|2 fast
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|a Safari, an O'Reilly Media Company.
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|u https://learning.oreilly.com/library/view/~/9781119561934/?ar
|z Texto completo (Requiere registro previo con correo institucional)
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|a 92
|b IZTAP
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