Hands-On Data Science with R

Techniques to perform data manipulation and mining to build smart analytical models using R

Häftad, Engelska, 2018

565 kr

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Beskrivning

A hands-on guide for professionals to perform various data science tasks in RKey FeaturesExplore the popular R packages for data scienceUse R for efficient data mining, text analytics and feature engineeringBecome a thorough data science professional with the help of hands-on examples and use-cases in RBook DescriptionR is the most widely used programming language, and when used in association with data science, this powerful combination will solve the complexities involved with unstructured datasets in the real world. This book covers the entire data science ecosystem for aspiring data scientists, right from zero to a level where you are confident enough to get hands-on with real-world data science problems.The book starts with an introduction to data science and introduces readers to popular R libraries for executing data science routine tasks. This book covers all the important processes in data science such as data gathering, cleaning data, and then uncovering patterns from it. You will explore algorithms such as machine learning algorithms, predictive analytical models, and finally deep learning algorithms. You will learn to run the most powerful visualization packages available in R so as to ensure that you can easily derive insights from your data.Towards the end, you will also learn how to integrate R with Spark and Hadoop and perform large-scale data analytics without much complexity.What you will learnUnderstand the R programming language and its ecosystem of packages for data scienceObtain and clean your data before processingMaster essential exploratory techniques for summarizing dataExamine various machine learning prediction, modelsExplore the H2O analytics platform in R for deep learningApply data mining techniques to available datasetsWork with interactive visualization packages in RIntegrate R with Spark and Hadoop for large-scale data analyticsWho this book is forIf you are a data analyst, data engineer, statistician or an R programmer and aspiring to enter the field of machine learning and predictive analytics, then this is the right book to start your journey. Basic understanding of linear algebra/statistics would be beneficial and R programming would be required.

Produktinformation

Utgivningsdatum:2018-11-30
Mått:191 x 235 x 23 mm
Vikt:780 g
Format:Häftad
Språk:Engelska
Antal sidor:420
Förlag:Packt Publishing Limited
ISBN:9781789139402

Utforska kategorier

Systemvetenskap och AI inom Data och IT
Databaser inom Data och IT

Mer om författaren

Doug Ortiz is an experienced enterprise cloud, big data, data analytics, and solutions architect who has architected, designed, developed, engineered, re-engineered, and integrated enterprise solutions. The technologies he has experience with include: Amazon Web Services, Azure, Google Cloud, Business Intelligence, Data Science, Hadoop, Spark, NoSQL and Graph Databases, and Web Front-End Technologies. Vitor Bianchi Lanzetta (@vitorlanzetta) has a master's degree in Applied Economics (University of So PauloUSP) and works as a data scientist in a tech start-up named RedFox Digital Solutions. He has also authored a book called R Data Visualization Recipes. The things he enjoys the most are statistics, economics, and sports of all kinds (electronics included). His blog, made in partnership with Ricardo Anjoleto Farias (@R_A_Farias), can be found at ArcadeData dot org, they kindly call it R-Cade Data. Nataraj Dasgupta is the vice president of advanced analytics at RxDataScience Inc. Nataraj has been in the IT industry for more than 19 years, and has worked in the technical and analytics divisions of Philip Morris, IBM, UBS Investment Bank, and Purdue Pharma. At Purdue Pharma, Nataraj led the data science division, where he developed the company's award-winning big data and machine learning platform. Prior to Purdue, at UBS, he held the role of Associate Director, working with high-frequency and algorithmic trading technologies in the foreign exchange trading division of the bank. Ricardo Anjoleto Farias is an economist who graduated from the Universidade Estadual de Maring in 2014. In addition to being a sports enthusiast (electronic or otherwise) and enjoying a good barbecue, he also likes math, statistics, and correlated studies. His first contact with R was when he embarked on his master's degree, and since then, he has tried to improve his skills with this powerful tool.

Innehållsförteckning

Table of ContentsGetting started withDescriptive and Inferential StatisticsData Wrangling with RKDD, Data Mining, and Text MiningData Analysis with RMachine Learning with RForecasting and ML App with RNeural Networks and Deep LearningMarkovian in RVisualizing DataGoing to Production with RLarge Scale Data Analytics with HadoopR on Cloud The Road Ahead

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