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Machine Learning With Spark And Python: Essential Techniques For Predictive...

Description: Please refer to the section BELOW (and NOT ABOVE) this line for the product details - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Title:Machine Learning With Spark And Python: Essential Techniques For Predictive AnalyticsISBN13:9781119561934ISBN10:1119561930Author:Bowles, Michael (Author)Description: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 Binding:Paperback, PaperbackPublisher:WileyPublication Date:2019-11-05Weight:1 lbsDimensions:0.9'' H x 9.2'' L x 7.3'' WNumber of Pages:368Language:English

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End Time: 2024-09-06T13:02:04.000Z

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Machine Learning With Spark And Python: Essential Techniques For Predictive...

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Book Title: Machine Learning With Spark And Python: Essential Techniques...

Item Length: 9in

Item Height: 0.9in

Item Width: 7.3in

Author: Michael Bowles

Publication Name: Machine Learning with Spark and Python : Essential Techniques for Predictive Analytics

Format: Trade Paperback

Language: English

Publisher: Wiley & Sons, Incorporated, John

Publication Year: 2019

Type: Textbook

Item Weight: 21.7 Oz

Number of Pages: 368 Pages

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