LEADER 03795nam 2200445 450 001 9910796533603321 005 20180929004705.0 035 $a(CKB)4100000000880863 035 \\$a(Safari)9781785886188 035 $a(OCoLC)994223065 035 $a(MiAaPQ)EBC4900799 035 $a(CaSebORM)9781785886188 035 $a(PPN)220205078 035 $a(EXLCZ)994100000000880863 100 $a20171020h20172017 uy 0 101 0 $aeng 135 $aurunu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aPractical predictive analytics $eback to the future with R, Spark, and more! /$fRalph Winters 205 $a1st edition 210 1$aBirmingham, [England] ;$aMumbai, [India] :$cPackt,$d2017. 210 4$dİ2017 215 $a1 online resource (1 volume) $cillustrations 300 $aIncludes index. 311 $a1-78588-046-2 311 $a1-78588-618-5 330 $aMake sense of your data and predict the unpredictable About This Book A unique book that centers around develop six key practical skills needed to develop and implement predictive analytics Apply the principles and techniques of predictive analytics to effectively interpret big data Solve 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 domains Who This Book Is For This 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 Learn Master the core predictive analytics algorithm which are used today in business Learn to implement the six steps for a successful analytics project Classify the right algorithm for your requirements Use and apply predictive analytics to research problems in healthcare Implement predictive analytics to retain and acquire your customers Use text mining to understand unstructured data Develop models on your own PC or in Spark/Hadoop environments Implement predictive analytics products for customers In Detail This 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 pre... 606 $aR (Computer program language) 615 0$aR (Computer program language) 676 $a519.502855133 700 $aWinters$b Ralph$01565891 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910796533603321 996 $aPractical predictive analytics$93835979 997 $aUNINA