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Bioinformatics with R Cookbook

Bioinformatics with R Cookbook Author Paurush Praveen Sinha
ISBN-10 9781783283149
Release 2014-06-23
Pages 340
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This book is an easy-to-follow, stepwise guide to handle real life Bioinformatics problems. Each recipe comes with a detailed explanation to the solution steps. A systematic approach, coupled with lots of illustrations, tips, and tricks will help you as a reader grasp even the trickiest of concepts without difficulty.This book is ideal for computational biologists and bioinformaticians with basic knowledge of R programming, bioinformatics and statistics. If you want to understand various critical concepts needed to develop your computational models in Bioinformatics, then this book is for you. Basic knowledge of R is expected.



Machine Learning with R Cookbook

Machine Learning with R Cookbook Author AshishSingh Bhatia
ISBN-10 9781787287808
Release 2017-10-23
Pages 572
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Explore over 110 recipes to analyze data and build predictive models with simple and easy-to-use R code About This Book Apply R to simplify predictive modeling with short and simple code Use machine learning to solve problems ranging from small to big data Build a training and testing dataset, applying different classification methods. Who This Book Is For This book is for data science professionals, data analysts, or people who have used R for data analysis and machine learning who now wish to become the go-to person for machine learning with R. Those who wish to improve the efficiency of their machine learning models and need to work with different kinds of data set will find this book very insightful. What You Will Learn Create and inspect transaction datasets and perform association analysis with the Apriori algorithm Visualize patterns and associations using a range of graphs and find frequent item-sets using the Eclat algorithm Compare differences between each regression method to discover how they solve problems Detect and impute missing values in air quality data Predict possible churn users with the classification approach Plot the autocorrelation function with time series analysis Use the Cox proportional hazards model for survival analysis Implement the clustering method to segment customer data Compress images with the dimension reduction method Incorporate R and Hadoop to solve machine learning problems on big data In Detail Big data has become a popular buzzword across many industries. An increasing number of people have been exposed to the term and are looking at how to leverage big data in their own businesses, to improve sales and profitability. However, collecting, aggregating, and visualizing data is just one part of the equation. Being able to extract useful information from data is another task, and a much more challenging one. Machine Learning with R Cookbook, Second Edition uses a practical approach to teach you how to perform machine learning with R. Each chapter is divided into several simple recipes. Through the step-by-step instructions provided in each recipe, you will be able to construct a predictive model by using a variety of machine learning packages. In this book, you will first learn to set up the R environment and use simple R commands to explore data. The next topic covers how to perform statistical analysis with machine learning analysis and assess created models, covered in detail later on in the book. You'll also learn how to integrate R and Hadoop to create a big data analysis platform. The detailed illustrations provide all the information required to start applying machine learning to individual projects. With Machine Learning with R Cookbook, machine learning has never been easier. Style and approach This is an easy-to-follow guide packed with hands-on examples of machine learning tasks. Each topic includes step-by-step instructions on tackling difficulties faced when applying R to machine learning.



Bioinformatics with Python Cookbook

Bioinformatics with Python Cookbook Author Tiago Antao
ISBN-10 9781783558650
Release 2015-06-25
Pages 306
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If you are either a computational biologist or a Python programmer, you will probably relate to the expression "explosive growth, exciting times". Python is arguably the main programming language for big data, and the deluge of data in biology, mostly from genomics and proteomics, makes bioinformatics one of the most exciting fields in data science. Using the hands-on recipes in this book, you'll be able to do practical research and analysis in computational biology with Python. We cover modern, next-generation sequencing libraries and explore real-world examples on how to handle real data. The main focus of the book is the practical application of bioinformatics, but we also cover modern programming techniques and frameworks to deal with the ever increasing deluge of bioinformatics data.



R for Data Science Cookbook

R for Data Science Cookbook Author Yu-Wei, Chiu (David Chiu)
ISBN-10 9781784392048
Release 2016-07-29
Pages 452
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Over 100 hands-on recipes to effectively solve real-world data problems using the most popular R packages and techniques About This Book Gain insight into how data scientists collect, process, analyze, and visualize data using some of the most popular R packages Understand how to apply useful data analysis techniques in R for real-world applications An easy-to-follow guide to make the life of data scientist easier with the problems faced while performing data analysis Who This Book Is For This book is for those who are already familiar with the basic operation of R, but want to learn how to efficiently and effectively analyze real-world data problems using practical R packages. What You Will Learn Get to know the functional characteristics of R language Extract, transform, and load data from heterogeneous sources Understand how easily R can confront probability and statistics problems Get simple R instructions to quickly organize and manipulate large datasets Create professional data visualizations and interactive reports Predict user purchase behavior by adopting a classification approach Implement data mining techniques to discover items that are frequently purchased together Group similar text documents by using various clustering methods In Detail This cookbook offers a range of data analysis samples in simple and straightforward R code, providing step-by-step resources and time-saving methods to help you solve data problems efficiently. The first section deals with how to create R functions to avoid the unnecessary duplication of code. You will learn how to prepare, process, and perform sophisticated ETL for heterogeneous data sources with R packages. An example of data manipulation is provided, illustrating how to use the “dplyr” and “data.table” packages to efficiently process larger data structures. We also focus on “ggplot2” and show you how to create advanced figures for data exploration. In addition, you will learn how to build an interactive report using the “ggvis” package. Later chapters offer insight into time series analysis on financial data, while there is detailed information on the hot topic of machine learning, including data classification, regression, clustering, association rule mining, and dimension reduction. By the end of this book, you will understand how to resolve issues and will be able to comfortably offer solutions to problems encountered while performing data analysis. Style and approach This easy-to-follow guide is full of hands-on examples of data analysis with R. Each topic is fully explained beginning with the core concept, followed by step-by-step practical examples, and concluding with detailed explanations of each concept used.



R Data Visualization Cookbook

R Data Visualization Cookbook Author Atmajitsinh Gohil
ISBN-10 9781783989515
Release 2015-01-29
Pages 236
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If you are a data journalist, academician, student or freelance designer who wants to learn about data visualization, this book is for you. Basic knowledge of R programming is expected.



R Cookbook

R Cookbook Author Paul Teetor
ISBN-10 9781449307264
Release 2011-03-03
Pages 438
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With more than 200 practical recipes, this book helps you perform data analysis with R quickly and efficiently. The R language provides everything you need to do statistical work, but its structure can be difficult to master. This collection of concise, task-oriented recipes makes you productive with R immediately, with solutions ranging from basic tasks to input and output, general statistics, graphics, and linear regression. Each recipe addresses a specific problem, with a discussion that explains the solution and offers insight into how it works. If you’re a beginner, R Cookbook will help get you started. If you’re an experienced data programmer, it will jog your memory and expand your horizons. You’ll get the job done faster and learn more about R in the process. Create vectors, handle variables, and perform other basic functions Input and output data Tackle data structures such as matrices, lists, factors, and data frames Work with probability, probability distributions, and random variables Calculate statistics and confidence intervals, and perform statistical tests Create a variety of graphic displays Build statistical models with linear regressions and analysis of variance (ANOVA) Explore advanced statistical techniques, such as finding clusters in your data "Wonderfully readable, R Cookbook serves not only as a solutions manual of sorts, but as a truly enjoyable way to explore the R language—one practical example at a time."—Jeffrey Ryan, software consultant and R package author



R Graphics Cookbook

R Graphics Cookbook Author Winston Chang
ISBN-10 9781449316952
Release 2013
Pages 396
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"Practical recipes for visualizing data"--Cover.



R Recipes for Analysis Visualization and Machine Learning

R  Recipes for Analysis  Visualization and Machine Learning Author Viswa Viswanathan
ISBN-10 9781787288799
Release 2016-11-24
Pages 959
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Get savvy with R language and actualize projects aimed at analysis, visualization and machine learning About This Book Proficiently analyze data and apply machine learning techniques Generate visualizations, develop interactive visualizations and applications to understand various data exploratory functions in R Construct a predictive model by using a variety of machine learning packages Who This Book Is For This Learning Path is ideal for those who have been exposed to R, but have not used it extensively yet. It covers the basics of using R and is written for new and intermediate R users interested in learning. This Learning Path also provides in-depth insights into professional techniques for analysis, visualization, and machine learning with R – it will help you increase your R expertise, regardless of your level of experience. What You Will Learn Get data into your R environment and prepare it for analysis Perform exploratory data analyses and generate meaningful visualizations of the data Generate various plots in R using the basic R plotting techniques Create presentations and learn the basics of creating apps in R for your audience Create and inspect the transaction dataset, performing association analysis with the Apriori algorithm Visualize associations in various graph formats and find frequent itemset using the ECLAT algorithm Build, tune, and evaluate predictive models with different machine learning packages Incorporate R and Hadoop to solve machine learning problems on big data In Detail The R language is a powerful, open source, functional programming language. At its core, R is a statistical programming language that provides impressive tools to analyze data and create high-level graphics. This Learning Path is chock-full of recipes. Literally! It aims to excite you with awesome projects focused on analysis, visualization, and machine learning. We'll start off with data analysis – this will show you ways to use R to generate professional analysis reports. We'll then move on to visualizing our data – this provides you with all the guidance needed to get comfortable with data visualization with R. Finally, we'll move into the world of machine learning – this introduces you to data classification, regression, clustering, association rule mining, and dimension reduction. This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products: R Data Analysis Cookbook by Viswa Viswanathan and Shanthi Viswanathan R Data Visualization Cookbook by Atmajitsinh Gohil Machine Learning with R Cookbook by Yu-Wei, Chiu (David Chiu) Style and approach This course creates a smooth learning path that will teach you how to analyze data and create stunning visualizations. The step-by-step instructions provided for each recipe in this comprehensive Learning Path will show you how to create machine learning projects with R.



Building Bioinformatics Solutions

Building Bioinformatics Solutions Author Conrad Bessant
ISBN-10 9780191643200
Release 2014-01-16
Pages 352
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Bioinformatics encompasses a broad and ever-changing range of activities involved with the management and analysis of data from molecular biology experiments. Despite the diversity of activities and applications, the basic methodology and core tools needed to tackle bioinformatics problems is common to many projects. This unique book provides an invaluable introduction to three of the main tools used in the development of bioinformatics software - Perl, R and MySQL - and explains how these can be used together to tackle the complex data-driven challenges that typify modern biology. These industry standard open source tools form the core of many bioinformatics projects, both in academia and industry. The methodologies introduced are platform independent, and all the examples that feature have been tested on Windows, Linux and Mac OS. Building Bioinformatics Solutions is suitable for graduate students and researchers in the life sciences who wish to automate analyses or create their own databases and web-based tools. No prior knowledge of software development is assumed. Having worked through the book, the reader should have the necessary core skills to develop computational solutions for their specific research programmes. The book will also help the reader overcome the inertia associated with penetrating this field, and provide them with the confidence and understanding required to go on to develop more advanced bioinformatics skills.



Odysseas

Odysseas Author James Joyce
ISBN-10 OCLC:31136650
Release 1971
Pages 1190
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Odysseas has been writing in one form or another for most of life. You can find so many inspiration from Odysseas also informative, and entertaining. Click DOWNLOAD or Read Online button to get full Odysseas book for free.



A Primer in Biological Data Analysis and Visualization Using R

A Primer in Biological Data Analysis and Visualization Using R Author Gregg Hartvigsen
ISBN-10 9780231537049
Release 2014-02-18
Pages 160
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R is a popular programming language that statisticians use to perform a variety of statistical computing tasks. Rooted in Gregg Hartvigsen's extensive experience teaching biology, this text is an engaging, practical, and lab-oriented introduction to R for students in the life sciences. Underscoring the importance of R and RStudio to the organization, computation, and visualization of biological statistics and data, Hartvigsen guides readers through the processes of entering data into R, working with data in R, and using R to express data in histograms, boxplots, barplots, scatterplots, before/after line plots, pie charts, and graphs. He covers data normality, outliers, and nonnormal data and examines frequently used statistical tests with one value and one sample; paired samples; more than two samples across a single factor; correlation; and linear regression. The volume also includes a section on advanced procedures and a final chapter on possible extensions into programming, featuring a discussion of algorithms, the art of looping, and combining programming and output.



Practical Data Science Cookbook

Practical Data Science Cookbook Author Prabhanjan Tattar
ISBN-10 9781787123267
Release 2017-06-29
Pages 434
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Over 85 recipes to help you complete real-world data science projects in R and Python About This Book Tackle every step in the data science pipeline and use it to acquire, clean, analyze, and visualize your data Get beyond the theory and implement real-world projects in data science using R and Python Easy-to-follow recipes will help you understand and implement the numerical computing concepts Who This Book Is For If you are an aspiring data scientist who wants to learn data science and numerical programming concepts through hands-on, real-world project examples, this is the book for you. Whether you are brand new to data science or you are a seasoned expert, you will benefit from learning about the structure of real-world data science projects and the programming examples in R and Python. What You Will Learn Learn and understand the installation procedure and environment required for R and Python on various platforms Prepare data for analysis by implement various data science concepts such as acquisition, cleaning and munging through R and Python Build a predictive model and an exploratory model Analyze the results of your model and create reports on the acquired data Build various tree-based methods and Build random forest In Detail As increasing amounts of data are generated each year, the need to analyze and create value out of it is more important than ever. Companies that know what to do with their data and how to do it well will have a competitive advantage over companies that don't. Because of this, there will be an increasing demand for people that possess both the analytical and technical abilities to extract valuable insights from data and create valuable solutions that put those insights to use. Starting with the basics, this book covers how to set up your numerical programming environment, introduces you to the data science pipeline, and guides you through several data projects in a step-by-step format. By sequentially working through the steps in each chapter, you will quickly familiarize yourself with the process and learn how to apply it to a variety of situations with examples using the two most popular programming languages for data analysis—R and Python. Style and approach This step-by-step guide to data science is full of hands-on examples of real-world data science tasks. Each recipe focuses on a particular task involved in the data science pipeline, ranging from readying the dataset to analytics and visualization



Practical Data Science Cookbook Second Edition

Practical Data Science Cookbook   Second Edition Author Prabhanjan Tattar
ISBN-10 1787129624
Release 2017-04-28
Pages 458
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89 hands-on recipes to help you complete real-world data science projects in R and PythonAbout This Book* Tackle every step in the data science pipeline and use it to acquire, clean, analyze, and visualize your data* Get beyond the theory and implement real-world projects in data science using R and Python* Easy-to-follow recipes will help you understand and implement the numerical computing conceptsWho This Book Is ForIf you are an aspiring data scientist who wants to learn data science and numerical programming concepts through hands-on, real-world project examples, this is the book for you. Whether you are brand new to data science or you are a seasoned expert, you will benefit from learning about the structure of real-world data science projects and the programming examples in R and Python.What you will learn* Get to know the installation procedure and environment required for R and Python on various platforms* Implement data science concepts such as acquisition, munging, and analysis through R and Python * Analyze and produce reports on data* Perform some text mining* Build a predictive model and an exploratory model* Build various tree-based methods and Build random forestIn DetailAs an increasing amount of data is generated each year, the need to analyze and operationalize it is more important than ever. Companies that know what to do with their data have a competitive advantage over companies that don't, and this drives a higher demand for knowledgeable and competent data professionals.Starting with the basics, this book covers how to set up your numerical programming environment, introduces you to the data science pipeline, and guides you through several data projects in a step-by-step format. By sequentially working through the steps in each chapter, you will quickly familiarize yourself with the process and learn how to apply it to a variety of situations with examples using the two most popular programming languages for data analysis-R and Python.



Biotechnology

Biotechnology Author Hans-Jürgen Rehm
ISBN-10 UOM:39015051315300
Release 2001
Pages
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Biotechnology has been writing in one form or another for most of life. You can find so many inspiration from Biotechnology also informative, and entertaining. Click DOWNLOAD or Read Online button to get full Biotechnology book for free.



Linux Powerful Server Administration

Linux  Powerful Server Administration Author Uday R. Sawant
ISBN-10 9781788297424
Release 2017-04-27
Pages 995
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Get hands-on recipes to make the most of Ubuntu Server, CentOS 7 Linux Server and RHEL 7 Server About This Book Get Linux servers up and running in seconds, In-depth guide to explore new features and solutions in server administration Maintain performance and security of your server solution by deploying expert configuration advice Who This Book Is For This Learning Path is intended for system administrators with a basic understanding of Linux operating systems and written with the novice-to-intermediate Linux user in mind. To get the most of this Learning Path, you should have a working knowledge of basic system administration and management tools. What You Will Learn Set up high performance, scalable, and fault-tolerant back ends with web and database servers Facilitate team communication with a real-time chat service and collaboration tools Monitor, manage and develop your server's file system to maintain a stable performance Gain best practice methods on sharing files and resources through a network Install and configure common standard services such as web, mail, FTP, database and domain name server technologies Create kickstart scripts to automatically deploy RHEL 7 systems Use Orchestration and configuration management tools to manage your environment In Detail Linux servers are frequently selected over other server operating systems for their stability, security and flexibility advantages.This Learning Path will teach you how to get up and running with three of the most popular Linux server distros: Ubuntu Server, CentOS 7 Server, and RHEL 7 Server. We will begin with the Ubuntu Server and show you how to make the most of Ubuntu's advanced functionalities. Moving on, we will provide you with all the knowledge that will give you access to the inner workings of the latest CentOS version 7. Finally, touching RHEL 7, we will provide you with solutions to common RHEL 7 Server challenges.This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products: 1) Ubuntu Server Cookbook 2) CentOS 7 Linux Server Cookbook, Second Edition 3) Red Hat Enterprise Linux Server Cookbook Style and approach This easy-to-follow practical guide contains hands on examples and solutions to real word administration problems and problems faced when building your RHEL 7 system from scratch using orchestration tools.



Books in Print 2009 2010

Books in Print 2009 2010 Author
ISBN-10 0835250199
Release 2009
Pages
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Books in Print 2009 2010 has been writing in one form or another for most of life. You can find so many inspiration from Books in Print 2009 2010 also informative, and entertaining. Click DOWNLOAD or Read Online button to get full Books in Print 2009 2010 book for free.



Products for Life Science Research

Products for Life Science Research Author Sigma Chemical Company
ISBN-10 STANFORD:36105123682630
Release 2008
Pages
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Products for Life Science Research has been writing in one form or another for most of life. You can find so many inspiration from Products for Life Science Research also informative, and entertaining. Click DOWNLOAD or Read Online button to get full Products for Life Science Research book for free.