Practical Predictive Analytics (notice n° 65501)

détails MARC
000 -LEADER
fixed length control field 03743cam a2200277zu 4500
003 - CONTROL NUMBER IDENTIFIER
control field FRCYB88842906
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20250107215859.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 250107s2017 fr | o|||||0|0|||eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781785886188
035 ## - SYSTEM CONTROL NUMBER
System control number FRCYB88842906
040 ## - CATALOGING SOURCE
Original cataloging agency FR-PaCSA
Language of cataloging en
Transcribing agency
Description conventions rda
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Winters, Ralph
245 01 - TITLE STATEMENT
Title Practical Predictive Analytics
Statement of responsibility, etc. ['Winters, Ralph']
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Name of producer, publisher, distributor, manufacturer Packt Publishing
Date of production, publication, distribution, manufacture, or copyright notice 2017
300 ## - PHYSICAL DESCRIPTION
Extent p.
336 ## - CONTENT TYPE
Content type code txt
Source rdacontent
337 ## - MEDIA TYPE
Media type code c
Source rdamdedia
338 ## - CARRIER TYPE
Carrier type code c
Source rdacarrier
520 ## - SUMMARY, ETC.
Summary, etc. Make sense of your data and predict the unpredictableAbout This BookA unique book that centers around develop six key practical skills needed to develop and implement predictive analyticsApply the principles and techniques of predictive analytics to effectively interpret big dataSolve real-world analytical problems with the help of practical case studies and real-world scenarios taken from the world of healthcare, marketing, and other business domainsWho This Book Is ForThis book is for those with a mathematical/statistics background who wish to understand the concepts, techniques, and implementation of predictive analytics to resolve complex analytical issues. Basic familiarity with a programming language of R is expected.What You Will LearnMaster the core predictive analytics algorithm which are used today in businessLearn to implement the six steps for a successful analytics projectClassify the right algorithm for your requirementsUse and apply predictive analytics to research problems in healthcareImplement predictive analytics to retain and acquire your customersUse text mining to understand unstructured dataDevelop models on your own PC or in Spark/Hadoop environmentsImplement predictive analytics products for customersIn DetailThis is the go-to book for anyone interested in the steps needed to develop predictive analytics solutions with examples from the world of marketing, healthcare, and retail. We'll get started with a brief history of predictive analytics and learn about different roles and functions people play within a predictive analytics project. Then, we will learn about various ways of installing R along with their pros and cons, combined with a step-by-step installation of RStudio, and a description of the best practices for organizing your projects.On completing the installation, we will begin to acquire the skills necessary to input, clean, and prepare your data for modeling. We will learn the six specific steps needed to implement and successfully deploy a predictive model starting from asking the right questions through model development and ending with deploying your predictive model into production. We will learn why collaboration is important and how agile iterative modeling cycles can increase your chances of developing and deploying the best successful model.We will continue your journey in the cloud by extending your skill set by learning about Databricks and SparkR, which allow you to develop predictive models on vast gigabytes of data.Style and ApproachThis book takes a practical hands-on approach wherein the algorithms will be explained with the help of real-world use cases. It is written in a well-researched academic style which is a great mix of theoretical and practical information. Code examples are supplied for both theoretical concepts as well as for the case studies. Key references and summaries will be provided at the end of each chapter so that you can explore those topics on their own.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element
700 0# - ADDED ENTRY--PERSONAL NAME
Personal name Winters, Ralph
856 40 - ELECTRONIC LOCATION AND ACCESS
Access method Cyberlibris
Uniform Resource Identifier <a href="https://international.scholarvox.com/netsen/book/88842906">https://international.scholarvox.com/netsen/book/88842906</a>
Electronic format type text/html
Host name

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