R Data Visualization Recipes
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R Data Visualization Cookbook
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Author : Atmajitsinh Gohil
language : en
Publisher: Packt Publishing Ltd
Release Date : 2015-01-29
R Data Visualization Cookbook written by Atmajitsinh Gohil and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-01-29 with Computers categories.
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 Data Visualization Recipes
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Author : Vitor Bianchi Lanzetta
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-11-22
R Data Visualization Recipes written by Vitor Bianchi Lanzetta and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-22 with Computers categories.
Translate your data into info-graphics using popular packages in R About This Book Use R's popular packages—such as ggplot2, ggvis, ggforce, and more—to create custom, interactive visualization solutions. Create, design, and build interactive dashboards using Shiny A highly practical guide to help you get to grips with the basics of data visualization techniques, and how you can implement them using R Who This Book Is For If you are looking to create custom data visualization solutions using the R programming language and are stuck somewhere in the process, this book will come to your rescue. Prior exposure to packages such as ggplot2 would be useful but not necessary. However, some R programming knowledge is required. What You Will Learn Get to know various data visualization libraries available in R to represent data Generate elegant codes to craft graphics using ggplot2, ggvis and plotly Add elements, text, animation, and colors to your plot to make sense of data Deepen your knowledge by adding bar-charts, scatterplots, and time series plots using ggplot2 Build interactive dashboards using Shiny. Color specific map regions based on the values of a variable in your data frame Create high-quality journal-publishable scatterplots Create and design various three-dimensional and multivariate plots In Detail R is an open source language for data analysis and graphics that allows users to load various packages for effective and better data interpretation. Its popularity has soared in recent years because of its powerful capabilities when it comes to turning different kinds of data into intuitive visualization solutions. This book is an update to our earlier R data visualization cookbook with 100 percent fresh content and covering all the cutting edge R data visualization tools. This book is packed with practical recipes, designed to provide you with all the guidance needed to get to grips with data visualization using R. It starts off with the basics of ggplot2, ggvis, and plotly visualization packages, along with an introduction to creating maps and customizing them, before progressively taking you through various ggplot2 extensions, such as ggforce, ggrepel, and gganimate. Using real-world datasets, you will analyze and visualize your data as histograms, bar graphs, and scatterplots, and customize your plots with various themes and coloring options. The book also covers advanced visualization aspects such as creating interactive dashboards using Shiny By the end of the book, you will be equipped with key techniques to create impressive data visualizations with professional efficiency and precision. Style and approach This book is packed with practical recipes, designed to provide you with all the guidance needed to get to grips with data visualization with R. You will learn to leverage the power of R and ggplot2 to create highly customizable data visualizations of varying complexities. The readers will then learn how to create, design, and build interactive dashboards using Shiny.
R Graphs Cookbook Second Edition
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Author : Jaynal Abedin
language : en
Publisher: Packt Publishing Ltd
Release Date : 2014-10-28
R Graphs Cookbook Second Edition written by Jaynal Abedin and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-10-28 with Computers categories.
Targeted at those with an existing familiarity with R programming, this practical guide will appeal directly to programmers interested in learning effective data visualization techniques with R and a wide-range of its associated libraries.
R Graphics Cookbook 2nd Edition
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Author : Winston Chang
language : en
Publisher:
Release Date : 2018
R Graphics Cookbook 2nd Edition written by Winston Chang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with R (Computer program language) categories.
The updated edition of this practical guide provides more than 150 recipes to help you generate high-quality graphs quickly, without having to comb through all the details of R’s graphing systems. Each recipe tackles a specific problem with a solution you can apply to your own project, and includes a discussion of how and why the recipe works. Most of the recipes in this edition use the updated version of the ggplot2 package, a powerful and flexible way to make graphs in R. You’ll also find expanded content about the visual design of graphics. If you have a basic understanding of the R language, you’re ready to get started. With Early Release ebooks, you get books in their earliest form — the author's raw and unedited content as he or she writes — so you can take advantage of these technologies long before the official release of these titles. You'll also receive updates when significant changes are made, new chapters are available, and the final ebook bundle is released.
Deep Learning Quick Reference
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Author : Michael Bernico
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-03-09
Deep Learning Quick Reference written by Michael Bernico and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-03-09 with Computers categories.
Dive deeper into neural networks and get your models trained, optimized with this quick reference guide Key Features A quick reference to all important deep learning concepts and their implementations Essential tips, tricks, and hacks to train a variety of deep learning models such as CNNs, RNNs, LSTMs, and more Supplemented with essential mathematics and theory, every chapter provides best practices and safe choices for training and fine-tuning your models in Keras and Tensorflow. Book Description Deep learning has become an essential necessity to enter the world of artificial intelligence. With this book deep learning techniques will become more accessible, practical, and relevant to practicing data scientists. It moves deep learning from academia to the real world through practical examples. You will learn how Tensor Board is used to monitor the training of deep neural networks and solve binary classification problems using deep learning. Readers will then learn to optimize hyperparameters in their deep learning models. The book then takes the readers through the practical implementation of training CNN's, RNN's, and LSTM's with word embeddings and seq2seq models from scratch. Later the book explores advanced topics such as Deep Q Network to solve an autonomous agent problem and how to use two adversarial networks to generate artificial images that appear real. For implementation purposes, we look at popular Python-based deep learning frameworks such as Keras and Tensorflow, Each chapter provides best practices and safe choices to help readers make the right decision while training deep neural networks. By the end of this book, you will be able to solve real-world problems quickly with deep neural networks. What you will learn Solve regression and classification challenges with TensorFlow and Keras Learn to use Tensor Board for monitoring neural networks and its training Optimize hyperparameters and safe choices/best practices Build CNN's, RNN's, and LSTM's and using word embedding from scratch Build and train seq2seq models for machine translation and chat applications. Understanding Deep Q networks and how to use one to solve an autonomous agent problem. Explore Deep Q Network and address autonomous agent challenges. Who this book is for If you are a Data Scientist or a Machine Learning expert, then this book is a very useful read in training your advanced machine learning and deep learning models. You can also refer this book if you are stuck in-between the neural network modeling and need immediate assistance in getting accomplishing the task smoothly. Some prior knowledge of Python and tight hold on the basics of machine learning is required.
R Graphics Cookbook
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Author : Winston Chang
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2012-12-06
R Graphics Cookbook written by Winston Chang and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.
This practical guide provides more than 150 recipes to help you generate high-quality graphs quickly, without having to comb through all the details of R’s graphing systems. Each recipe tackles a specific problem with a solution you can apply to your own project, and includes a discussion of how and why the recipe works. Most of the recipes use the ggplot2 package, a powerful and flexible way to make graphs in R. If you have a basic understanding of the R language, you’re ready to get started. Use R’s default graphics for quick exploration of data Create a variety of bar graphs, line graphs, and scatter plots Summarize data distributions with histograms, density curves, box plots, and other examples Provide annotations to help viewers interpret data Control the overall appearance of graphics Render data groups alongside each other for easy comparison Use colors in plots Create network graphs, heat maps, and 3D scatter plots Structure data for graphing
Ggplot2 Essentials
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Author : Donato Teutonico
language : en
Publisher: Packt Publishing Ltd
Release Date : 2015-06-25
Ggplot2 Essentials written by Donato Teutonico and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-06-25 with Computers categories.
ggplot2 is one of the most sophisticated and advanced packages of R and its use is constantly growing in the community of R programmers. This book is the perfect starting point for your journey in learning about one of the most refined and widely used plotting tools—ggplot2. You will start by taking a tour of the most relevant packages available in R to create plots, such as graphics, lattice, and ggplot2. Following this, you will take a deep dive into the concepts of ggplot2 by covering different kinds of plots that will help you gear up for your first hands-on project. After this first taste of the capabilities of ggplot2, you will explore in detail the visualization approach implemented in this package, the so-called grammar of graphics, providing you with the basics to understand the backstage concepts in the plotting functions. Finally, you will take a look at some specialized and sophisticated applications of ggplot2, such as how to realize a complex scatterplot matrix, heatmaps, and how to make spatial visualization graphs.
R Recipes For Analysis Visualization And Machine Learning
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Author : Viswa Viswanathan
language : en
Publisher: Packt Publishing Ltd
Release Date : 2016-11-24
R Recipes For Analysis Visualization And Machine Learning written by Viswa Viswanathan and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-24 with Computers categories.
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.
Data Visualization Techniques
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Author : Chandrajit Bajaj
language : en
Publisher:
Release Date : 1999
Data Visualization Techniques written by Chandrajit Bajaj and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with Computers categories.
Data visualization techniques are a means to manipulate sampled and computed data for comprehensive display. Visualized data can be static or in motion, to provide visual explanations of algorithms or general information. This book draws on examples from a broad selection of subject areas, such as atmospheric sciences or biology, which deal with diverse data analysis and visualization techniques. The various visualization methodologies covered in this book also include moving images as well as static. It is an important source of information for computer graphics software engineers, graduates and researchers who work in the field of visualization techniques. Unique features in this book include: Details of data visualization techniques for scalar, vector and tensor field data and accompanying data structures Explanation of how to express visual images in computational terms and turn these into display, with minimum delay Methodology for "probing" a displayed visualization, in order to elicit more detail Collection of information from several interrelated subject areas in one volume Trends in Software - edited by Balachander Krishnamurthy of AT&T Research - is a sister publication of the journal Software: Practice and Experience
R
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Author : Viswa Viswanathan
language : en
Publisher:
Release Date : 2016
R written by Viswa Viswanathan and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with Machine learning categories.