Showing results for "robert knell"
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2014
EN
R is now the most widely used statistical software in academic science and it is rapidly expanding into other fields such as finance. R is almost limitlessly flexible and powerful, hence its appeal, but can be very difficult for the novice user. There are no easy pull-down menus, error messages are often cryptic and simple tasks like importing your data or exporting a graph can be difficult and frustrating. Introductory R is written for the novice user who knows a little about statistics b...
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R for Everyone
Advanced Analytics and Graphics
2013
EN
Statistical Computation for Programmers, Scientists, Quants, Excel Users, and Other ProfessionalsUsing the open source R language, you can build powerful statistical models to answer many of your most challenging questions. R has traditionally been difficult for non-statisticians to learn, and most R books assume far too much knowledge to be of help. R for Everyone is the solution.Drawing on his unsurpassed experience teaching new users, professional data s...
Learning OpenCV
Computer Vision with the OpenCV Library
2008
EN
"This library is useful for practitioners, and is an excellent tool for those entering the field: it is a set of computer vision algorithms that work as advertised."-William T. Freeman, Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of TechnologyLearning OpenCV puts you in the middle of the rapidly expanding field of computer vision. Written by the creators of the free open source OpenCV library, this book introduces you to computer vision...
Python Machine Learning
Learn how to build powerful Python machine learning algorithms to generate useful data insights with this data analysis tutorial
2015
EN
Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analyticsKey FeaturesLeverage Python’s most powerful open-source libraries for deep learning, data wrangling, and data visualizationLearn effective strategies and best practices to improve and optimize machine learning systems and algorithmsAsk – and answer – tough questions of your data with robust statistical models, built for a range of datasets...
Machine Learning with R
R gives you access to the cutting-edge software you need to prepare data for machine learning. No previous knowledge required – this book will take you methodically through every stage of applying machine learning.
2013
EN
Written as a tutorial to explore and understand the power of R for machine learning. This practical guide that covers all of the need to know topics in a very systematic way. For each machine learning approach, each step in the process is detailed, from preparing the data for analysis to evaluating the results. These steps will build the knowledge you need to apply them to your own data science tasks.Intended for those who want to learn how to use R's machine learning capabilities and gain...
1998
EN
Most books on data structures assume an imperative language like C or C++. However, data structures for these languages do not always translate well to functional languages such as Standard ML, Haskell, or Scheme. This book describes data structures from the point of view of functional languages, with examples, and presents design techniques so that programmers can develop their own functional data structures. It includes both classical data structures, such as red-black trees and binomial...
R in a Nutshell
A Desktop Quick Reference
2012
EN
If you’re considering R for statistical computing and data visualization, this book provides a quick and practical guide to just about everything you can do with the open source R language and software environment. You’ll learn how to write R functions and use R packages to help you prepare, visualize, and analyze data. Author Joseph Adler illustrates each process with a wealth of examples from medicine, business, and sports.Updated for R 2.14 and 2.15, this second edition includes...
Mathematica Cookbook
Building Blocks for Science, Engineering, Finance, Music, and More
2010
EN
Mathematica Cookbook helps you master the application's core principles by walking you through real-world problems. Ideal for browsing, this book includes recipes for working with numerics, data structures, algebraic equations, calculus, and statistics. You'll also venture into exotic territory with recipes for data visualization using 2D and 3D graphic tools, image processing, and music.Although Mathematica 7 is a highly advanced computational platform, the recipes in thi...
Statistics for Ecologists Using R and Excel
Data Collection, Exploration, Analysis and Presentation
- Book 1 -
- Data in the Wild
2012
EN
This is a book about the scientific process and how we apply it to data in ecology. We will learn how to plan for data collection, how to assemble data, how to analyse data and finally how to present the results. The book uses Microsoft Excel and the powerful Open Source R program to carry out data handling as well as producing graphs. Who this book is for Students of ecology and environmental science will find this book aimed at them although many other scientists will find the text usefu...
ggplot2
Elegant Graphics for Data Analysis
2016
EN
This new edition to the classic book by ggplot2 creator Hadley Wickham highlights compatibility with knitr and RStudio. ggplot2 is a data visualization package for R that helps users create data graphics, including those that are multi-layered, with ease. With ggplot2, it's easy to:produce handsome, publication-quality plots with automatic legends created from the plot specificationsuperimpose multiple layers (points, lines, maps, tiles, box plots) from different da...
2014
EN
Using R for Statistics will get you the answers to most of the problems you are likely to encounter when using a variety of statistics. This book is a problem-solution primer for using R to set up your data, pose your problems and get answers using a wide array of statistical tests. The book walks you through R basics and how to use R to accomplish a wide variety statistical operations.You'll be able to navigate the R system, enter and import data, manipulate datasets, ca...











