R: predictive analysis : master the art of predictive modeling
Master the art of predictive modeling About This Book Load, wrangle, and analyze your data using the world's most powerful statistical programming language Familiarize yourself with the most common data mining tools of R, such as k-means, hierarchical regression, linear regression, Naïve Bayes...
Gespeichert in:
| Beteiligte Personen: | , , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
Birmingham, UK
Packt Publishing
2017
|
| Schlagwörter: | |
| Links: | https://learning.oreilly.com/library/view/-/9781788290371/?ar |
| Zusammenfassung: | Master the art of predictive modeling About This Book Load, wrangle, and analyze your data using the world's most powerful statistical programming language Familiarize yourself with the most common data mining tools of R, such as k-means, hierarchical regression, linear regression, Naïve Bayes, decision trees, text mining and so on. We emphasize important concepts, such as the bias-variance trade-off and over-fitting, which are pervasive in predictive modeling Who This Book Is For If you work with data and want to become an expert in predictive analysis and modeling, then this Learning Path will serve you well. It is intended for budding and seasoned practitioners of predictive modeling alike. You should have basic knowledge of the use of R, although it's not necessary to put this Learning Path to great use. What You Will Learn Get to know the basics of R's syntax and major data structures Write functions, load data, and install packages Use different data sources in R and know how to interface with databases, and request and load JSON and XML Identify the challenges and apply your knowledge about data analysis in R to imperfect real-world data Predict the future with reasonably simple algorithms Understand key data visualization and predictive analytic skills using R Understand the language of models and the predictive modeling process In Detail Predictive analytics is a field that uses data to build models that predict a future outcome of interest. It can be applied to a range of business strategies and has been a key player in search advertising and recommendation engines. The power and domain-specificity of R allows the user to express complex analytics easily, quickly, and succinctly. R offers a free and open source environment that is perfect for both learning and deploying predictive modeling solutions in the real world. This Learning Path will provide you with all the steps you need to master the art of predictive modeling with R. We start with an introduction to data analysis with R, and then gradually you'll get your feet wet with predictive modeling. You will get to grips with the fundamentals of applied statistics and build on this knowledge to perform sophisticated and powerful analytics. You will be able to solve the difficulties relating to performing data analysis in practice and find solutions to working with ?messy data?, large data, communicating results, and facilitating reproducibility. You will then perform key predictive... |
| Beschreibung: | "Learning path.". - Includes bibliographical references and index. - Description based on online resource; title from cover (viewed April 18, 2017) |
| Umfang: | 1 Online-Ressource (1 volume) illustrations |
| ISBN: | 9781788290852 1788290852 9781788290371 |
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| spelling | Fischetti, Tony VerfasserIn aut R predictive analysis : master the art of predictive modeling Tony Fischetti, Eric Mayor, Rui Miguel Birmingham, UK Packt Publishing 2017 1 Online-Ressource (1 volume) illustrations Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier "Learning path.". - Includes bibliographical references and index. - Description based on online resource; title from cover (viewed April 18, 2017) Master the art of predictive modeling About This Book Load, wrangle, and analyze your data using the world's most powerful statistical programming language Familiarize yourself with the most common data mining tools of R, such as k-means, hierarchical regression, linear regression, Naïve Bayes, decision trees, text mining and so on. We emphasize important concepts, such as the bias-variance trade-off and over-fitting, which are pervasive in predictive modeling Who This Book Is For If you work with data and want to become an expert in predictive analysis and modeling, then this Learning Path will serve you well. It is intended for budding and seasoned practitioners of predictive modeling alike. You should have basic knowledge of the use of R, although it's not necessary to put this Learning Path to great use. What You Will Learn Get to know the basics of R's syntax and major data structures Write functions, load data, and install packages Use different data sources in R and know how to interface with databases, and request and load JSON and XML Identify the challenges and apply your knowledge about data analysis in R to imperfect real-world data Predict the future with reasonably simple algorithms Understand key data visualization and predictive analytic skills using R Understand the language of models and the predictive modeling process In Detail Predictive analytics is a field that uses data to build models that predict a future outcome of interest. It can be applied to a range of business strategies and has been a key player in search advertising and recommendation engines. The power and domain-specificity of R allows the user to express complex analytics easily, quickly, and succinctly. R offers a free and open source environment that is perfect for both learning and deploying predictive modeling solutions in the real world. This Learning Path will provide you with all the steps you need to master the art of predictive modeling with R. We start with an introduction to data analysis with R, and then gradually you'll get your feet wet with predictive modeling. You will get to grips with the fundamentals of applied statistics and build on this knowledge to perform sophisticated and powerful analytics. You will be able to solve the difficulties relating to performing data analysis in practice and find solutions to working with ?messy data?, large data, communicating results, and facilitating reproducibility. You will then perform key predictive... R (Computer program language) Quantitative research Data mining R (Langage de programmation) Recherche quantitative Exploration de données (Informatique) COMPUTERS / Databases / Data Mining COMPUTERS / Programming Languages / General Mayor, Eric VerfasserIn aut Forte, Rui Miguel VerfasserIn aut 9781788290371 Erscheint auch als Druck-Ausgabe 9781788290371 |
| spellingShingle | Fischetti, Tony Mayor, Eric Forte, Rui Miguel R predictive analysis : master the art of predictive modeling R (Computer program language) Quantitative research Data mining R (Langage de programmation) Recherche quantitative Exploration de données (Informatique) COMPUTERS / Databases / Data Mining COMPUTERS / Programming Languages / General |
| title | R predictive analysis : master the art of predictive modeling |
| title_auth | R predictive analysis : master the art of predictive modeling |
| title_exact_search | R predictive analysis : master the art of predictive modeling |
| title_full | R predictive analysis : master the art of predictive modeling Tony Fischetti, Eric Mayor, Rui Miguel |
| title_fullStr | R predictive analysis : master the art of predictive modeling Tony Fischetti, Eric Mayor, Rui Miguel |
| title_full_unstemmed | R predictive analysis : master the art of predictive modeling Tony Fischetti, Eric Mayor, Rui Miguel |
| title_short | R |
| title_sort | r predictive analysis master the art of predictive modeling |
| title_sub | predictive analysis : master the art of predictive modeling |
| topic | R (Computer program language) Quantitative research Data mining R (Langage de programmation) Recherche quantitative Exploration de données (Informatique) COMPUTERS / Databases / Data Mining COMPUTERS / Programming Languages / General |
| topic_facet | R (Computer program language) Quantitative research Data mining R (Langage de programmation) Recherche quantitative Exploration de données (Informatique) COMPUTERS / Databases / Data Mining COMPUTERS / Programming Languages / General |
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