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[null,"1.","Record Nr.",null,"UNINA9910797539903321"]
[null,null,"Autore",null,"Garner Henry"]
[null,null,"Titolo",null,"Clojure for data science : statistics, big data, and machine learning for Clojure programmers / / Henry Garner"]
[null,null,"Pubbl/distr/stampa",null,"Birmingham : , : Packt Publishing, , 2015"]
[null,null,"ISBN",null,"1-78439-750-4"]
[null,null,"Edizione",null,"[1st edition]"]
[null,null,"Descrizione fisica",null,"1 online resource (608 p.)"]
[null,null,"Collana",null,"Community experience distilled"]
[null,null,"Soggetti",null,"Clojure (Computer program language)"]
[{"$nulls":4},"Big data"]
[{"$nulls":4},"Machine learning"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Includes index."]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,null,"Sommario/riassunto","Statistics, big data, and machine learning for Clojure programmers About This Book Write code using Clojure to harness the power of your data Discover the libraries and frameworks that will help you succeed A practical guide to understanding how the Clojure programming language can be used to derive insights from data Who This Book Is For This book is aimed at developers who are already productive in Clojure but who are overwhelmed by the breadth and depth of understanding required to be effective in the field of data science. Whether you're tasked with delivering a specific analytics project or simply suspect that you could be deriving more value from your data, this book will inspire you with the opportunities?and inform you of the risks?that exist in data of all shapes and sizes. What You Will Learn Perform hypothesis testing and understand feature selection and statistical significance to interpret your results with confidence Implement the core machine learning techniques of regression, classification, clustering and recommendation Understand the importance of the value of simple statistics and distributions in exploratory data analysis Scale algorithms to web-sized datasets efficiently using distributed programming models on Hadoop and Spark Apply suitable analytic approaches for text, graph, and time series data Interpret the terminology that you will encounter in technical papers Import libraries from other JVM languages such as Java and Scala Communicate your findings clearly and convincingly to nontechnical colleagues In Detail The term ?data "]
[{"$nulls":4},"science? has been widely used to define this new profession that is expected to interpret vast datasets and translate them to improved decision-making and performance. Clojure is a powerful language that combines the interactivity of a scripting language with the speed of a compiled language. Together with its rich ecosystem of native libraries and an extremely simple and consistent functional approach to data manipulation, which maps closely to mathematical formula, it is an ideal, practical, and flexible language to meet a data scientist's diverse needs. Taking you on a journey from simple summary statistics to sophisticated machine learning algorithms, this book shows how the Clojure programming language can be used to derive insights from data. Data scientists often forge a novel path, and you'll see how to make use of Clojure's Java interoperability capabilities to access libraries such as ..."]