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  • Mailund, Thomas  (5)
  • Vohra, Deepak  (3)
  • [Place of publication not identified] : Apress  (8)
  • Electronic books ; local  (8)
  • Apache Hadoop  (2)
  • 1
    Online Resource
    Online Resource
    Domain-specific languages in R : advanced statistical programming (2018)
    [Place of publication not identified] : Apress
    Details
    ISBN: 9781484235881
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: R (Computer program language) ; Domain-specific programming languages ; Electronic books ; local ; Electronic books
    Abstract: Gain an accelerated introduction to domain-specific languages in R, including coverage of regular expressions. This compact, in-depth book shows you how DSLs are programming languages specialized for a particular purpose, as opposed to general purpose programming languages. Along the way, you'll learn to specify tasks you want to do in a precise way and achieve programming goals within a domain-specific context. Domain-Specific Languages in R includes examples of DSLs including large data sets or matrix multiplication; pattern matching DSLs for application in computer vision; and DSLs for continuous time Markov chains and their applications in data science. After reading and using this book, you'll understand how to write DSLs in R and have skills you can extrapolate to other programming languages. What You'll Learn Program with domain-specific languages using R Discover the components of DSLs Carry out large matrix expressions and multiplications Implement metaprogramming with DSLs Parse and manipulate expressions Who This Book Is For Those with prior programming experience. R knowledge is helpful but not required.
    Note: Includes bibliographical references. - Description based on online resource; title from cover (Safari, viewed July 18, 2018)
    URL: lizenzpflichtig
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    Online Resource
    MPI Ethno. Forsch.
  • 2
    Online Resource
    Online Resource
    Functional programming in R : advanced statistical programming for data science, analysis and finance (2017)
    [Place of publication not identified] : Apress
    Details
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Functional programming (Computer science) ; R (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Master functions and discover how to write functional programs in R. In this concise book, you'll make your functions pure by avoiding side-effects; you'll write functions that manipulate other functions, and you'll construct complex functions using simpler functions as building blocks. In Functional Programming in R , you'll see how we can replace loops, which can have side-effects, with recursive functions that can more easily avoid them. In addition, the book covers why you shouldn't use recursion when loops are more efficient and how you can get the best of both worlds. Functional programming is a style of programming, like object-oriented programming, but one that focuses on data transformations and calculations rather than objects and state. Where in object-oriented programming you model your programs by describing which states an object can be in and how methods will reveal or modify that state, in functional programming you model programs by describing how functions translate input data to output data. Functions themselves are considered to be data you can manipulate and much of the strength of functional programming comes from manipulating functions; that is, building more complex functions by combining simpler functions. What You'll Learn Write functions in R including infix operators and replacement functions Create higher order functions Pass functions to other functions and start using functions as data you can manipulate Use Filer, Map and Reduce functions to express the intent behind code clearly and safely Build new functions from existing functions without necessarily writing any new functions, using point-free programming Create functions that carry data along with them Who This Book Is For Those with at least some experience with programming in R.
    Note: Description based on online resource; title from cover (Safari, viewed April 18, 2017)
    URL: https://learning.oreilly.com/library/view/-/9781484227466/?ar
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    Online Resource
    MPI Ethno. Forsch.
  • 3
    Online Resource
    Online Resource
    Advanced object-oriented programming in R : statistical programming for data science, analysis and finance (2017)
    [Place of publication not identified] : Apress
    Details
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: R (Computer program language) ; Object-oriented programming (Computer science) ; Electronic books ; Electronic books ; local
    Abstract: Learn how to write object-oriented programs in R and how to construct classes and class hierarchies in the three object-oriented systems available in R. This book gives an introduction to object-oriented programming in the R programming language and shows you how to use and apply R in an object-oriented manner. You will then be able to use this powerful programming style in your own statistical programming projects to write flexible and extendable software. After reading Advanced Object-Oriented Programming in R , you'll come away with a practical project that you can reuse in your own analytics coding endeavors. You'll then be able to visualize your data as objects that have state and then manipulate those objects with polymorphic or generic methods. Your projects will benefit from the high degree of flexibility provided by polymorphism, where the choice of concrete method to execute depends on the type of data being manipulated. What You'll Learn Define and use classes and generic functions using R Work with the R class hierarchies Benefit from implementation reuse Handle operator overloading Apply the S4 and R6 classes Who This Book Is For Experienced programmers and for those with at least some prior experience with R programming language.
    Note: Description based on online resource; title from cover (Safari, viewed September 29, 2017)
    URL: https://learning.oreilly.com/library/view/-/9781484229187/?ar
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  • 4
    Online Resource
    Online Resource
    Metaprogramming in R : advanced statistical programming for data science, analysis and finance (2017)
    [Place of publication not identified] : Apress
    Details
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: R (Computer program language) ; Computer programming ; Mathematical statistics ; Electronic books ; Electronic books ; local
    Abstract: Learn how to manipulate functions and expressions to modify how the R language interprets itself. This book is an introduction to metaprogramming in the R language, so you will write programs to manipulate other programs. Metaprogramming in R shows you how to treat code as data that you can generate, analyze, or modify. R is a very high-level language where all operations are functions and all functions are data that can be manipulated. This book shows you how to leverage R's natural flexibility in how function calls and expressions are evaluated, to create small domain-specific languages to extend R within the R language itself. What You'll Learn Find out about the anatomy of a function in R Look inside a function call Work with R expressions and environments Manipulate expressions in R Use substitutions Who This Book Is For Those with at least some experience with R and certainly for those with experience in other programming languages
    Note: Description based on online resource; title from cover page (Safari, viewed September 29, 2017)
    URL: https://learning.oreilly.com/library/view/-/9781484228814/?ar
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  • 5
    Online Resource
    Online Resource
    Beginning data science in R : data analysis, visualization, and modelling for the data scientist (2017)
    [Place of publication not identified] : Apress
    Details
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Quantitative research ; R (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Discover best practices for data analysis and software development in R and start on the path to becoming a fully-fledged data scientist. This book teaches you techniques for both data manipulation and visualization and shows you the best way for developing new software packages for R. Beginning Data Science in R details how data science is a combination of statistics, computational science, and machine learning. You'll see how to efficiently structure and mine data to extract useful patterns and build mathematical models. This requires computational methods and programming, and R is an ideal programming language for this. This book is based on a number of lecture notes for classes the author has taught on data science and statistical programming using the R programming language. Modern data analysis requires computational skills and usually a minimum of programming. What You Will Learn Perform data science and analytics using statistics and the R programming language Visualize and explore data, including working with large data sets found in big data Build an R package Test and check your code Practice version control Profile and optimize your code Who This Book Is For Those with some data science or analytics background, but not necessarily experience with the R programming language.
    Note: Description based on online resource; title from cover (Safari, viewed April 18, 2017)
    URL: https://learning.oreilly.com/library/view/-/9781484226711/?ar
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  • 6
    Online Resource
    Online Resource
    Docker management design patterns : swarm mode on Amazon Web Services (2017)
    [Place of publication not identified] : Apress
    Details
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Amazon Web Services (Firm) ; Cloud computing ; Virtual computer systems ; Application software ; Development ; Software patterns ; Electronic books ; Electronic books ; local
    Abstract: Master every aspect of orchestrating/managing Docker including creating a Swarm, creating services, using mounts, scheduling, scaling, resource management, rolling updates, load balancing, high availability, logging and monitoring, using multiple zones, and networking. This book also discusses the managed services for Docker Swarm: Docker for AWS and Docker Cloud Swarm mode. Docker Management Design Patterns explains how to use Docker Swarm mode with Docker Engine to create a distributed Docker container cluster and how to scale a cluster of containers, schedule containers on specific nodes, and mount a volume. This book is based on the latest version of Docker (17.0x). You will learn to provision a Swarm on production-ready AWS EC2 nodes, and to link Docker Cloud to Docker for AWS to provision a new Swarm or connect to an existing Swarm. Finally, you will learn to deploy a Docker Stack on Docker Swarm with Docker Compose. What You'll Learn Apply Docker management design patterns Use Docker Swarm mode and other new features Create and scale a Docker service Use mounts including volumes Configure scheduling, load balancing, high availability, logging and monitoring, rolling updates, resource management, and networking Use Docker for AWS managed services including a multi-zone Swarm Build Docker Cloud managed services in Swarm mode Who This Book Is For Docker admins, Docker application developers, and container as a service (CAAS) developers. Some prerequisite knowledge of Linux and Docker is required. Apress Pro Docker is recommended as a companion to this book.
    Note: Description based on online resource; title from cover (Safari, viewed November 28, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781484229736/?ar
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  • 7
    Online Resource
    Online Resource
    Apache HBase primer (2016)
    [Place of publication not identified] : Apress
    Details
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Apache Hadoop ; Databases ; Open source software ; Electronic books ; Electronic books ; local
    Abstract: Learn the fundamental foundations and concepts of the Apache HBase (NoSQL) open source database. It covers the HBase data model, architecture, schema design, API, and administration. Apache HBase is the database for the Apache Hadoop framework. HBase is a column family based NoSQL database that provides a flexible schema model. What You'll Learn Work with the core concepts of HBase Discover the HBase data model, schema design, and architecture Use the HBase API and administration Who This Book Is For Apache HBase (NoSQL) database users, designers, developers, and admins.
    Note: Description based on online resource; title from cover (Safari, viewed February 1, 2017)
    URL: https://learning.oreilly.com/library/view/-/9781484224243/?ar
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  • 8
    Online Resource
    Online Resource
    Practical Hadoop ecosystem : a definitive guide to Hadoop-related frameworks and tools (2016)
    [Place of publication not identified] : Apress
    Details
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Apache Hadoop ; Database management ; Electronic books ; Electronic books ; local
    Abstract: Learn how to use the Apache Hadoop projects, including MapReduce, HDFS, Apache Hive, Apache HBase, Apache Kafka, Apache Mahout, and Apache Solr. From setting up the environment to running sample applications each chapter in this book is a practical tutorial on using an Apache Hadoop ecosystem project. While several books on Apache Hadoop are available, most are based on the main projects, MapReduce and HDFS, and none discusses the other Apache Hadoop ecosystem projects and how they all work together as a cohesive big data development platform. What You Will Learn: Set up the environment in Linux for Hadoop projects using Cloudera Hadoop Distribution CDH 5 Run a MapReduce job Store data with Apache Hive, and Apache HBase Index data in HDFS with Apache Solr Develop a Kafka messaging system Stream Logs to HDFS with Apache Flume Transfer data from MySQL database to Hive, HDFS, and HBase with Sqoop Create a Hive table over Apache Solr Develop a Mahout User Recommender System Who This Book Is For: Apache Hadoop developers. Pre-requisite knowledge of Linux and some knowledge of Hadoop is required.
    Note: Description based on online resource; title from cover (Safari, viewed November 22, 2016)
    URL: https://learning.oreilly.com/library/view/-/9781484221990/?ar
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