R: Data Analysis and Visualization

R: Data Analysis and Visualization

English | ISBN: 1786460483, ASIN: B01HOB5IRM | 2016 | PDF/EPUB/MOBI/Code files | 1783 Pages | 332 MB

Master the art of building analytical models using R

About This Book
Load, wrangle, and analyze your data using the world's most powerful statistical programming language
Build and customize publication-quality visualizations of powerful and stunning R graphs
Develop key skills and techniques with R to create and customize data mining algorithms
Use R to optimize your trading strategy and build up your own risk management system
Discover how to build machine learning algorithms, prepare data, and dig deep into data prediction techniques with R
Who This Book Is For
This course is for data scientist or quantitative analyst who are looking at learning R and take advantage of its powerful analytical design framework. It's a seamless journey in becoming a full-stack R developer

What You Will Learn
Describe and visualize the behavior of data and relationships between data
Gain a thorough understanding of statistical reasoning and sampling
Handle missing data gracefully using multiple imputation
Create diverse types of bar charts using the default R functions
Familiarize yourself with algorithms written in R for spatial data mining, text mining, and so on
Understand relationships between market factors and their impact on your portfolio
Harness the power of R to build machine learning algorithms with real-world data science applications
Learn specialized machine learning techniques for text mining, big data, and more

In Detail
The R learning path created for you has five connected modules,which are a mini-course in their own right.As you complete each one, you'll have gained key skills and be ready for the material in the next module!

This course begins by looking at the Data Analysis with R module. This will help you navigate the R environment. You'll gain a thorough understanding of statistical reasoning and sampling. Finally, you'll be able to put best practices into effect to make your job easier and facilitate reproducibility.

The second place to explore is R Graphs,which will help you leverage powerful default R graphics and utilize advanced graphics systems such as lattice and ggplot2, the grammar of graphics. Through inspecting large datasets using tableplot and stunning 3D visualizations, you will know how to produce, customize, and publish advanced visualizations using this popular and powerful framework.

With the third module, Learning Data Mining with R, you will learn how to manipulate data with R using code snippets and be introduced to mining frequent patterns, association, and correlations while working with R programs. You will finish this module feeling confident in your ability to know which data mining algorithm to apply in any situation.

The Mastering R for Quantitative Finance module pragmatically introduces both the quantitative finance concepts and their modeling in R, enabling you to build a tailor-made trading system on your own. By the end of the module, you will be well-versed with various financial techniques using R and will be able to place good bets while making financial decisions.

Finally, we'll look at the Machine Learning with R module. With this module, you'll discover all the analytical tools you need to gain insights from complex data and learn how to choose the correct algorithm for your specific needs. You'll also learn to apply machine learning methods to deal with common tasks, including classification, prediction, forecasting, market analysis, and clustering.

Style and approach
Learn data analysis, data visualization techniques, data mining, and machine learning all using R and also learn to build models in quantitative finance using this powerful language



[Fast Download] R: Data Analysis and Visualization

Ebooks related to "R: Data Analysis and Visualization" :
Hive Succinctly
Azure Cosmos DB and DocumentDB Succinctly
Entity Framework Code First Succinctly
SQL on Azure Succinctly
Entity Framework Core Succinctly
Conquering Big Data with High Performance Computing
Internet of Things and Big Data Technologies for Next Generation Healthcare
Text Mining with MATLAB?
Combinatorial Maps: Efficient Data Structures for Computer Graphics and Image Processing
Exchanging Data Between SAS and Microsoft Excel: Tips and Techniques to Transfer and Manage Data Mor
Copyright Disclaimer:
This site does not store any files on its server. We only index and link to content provided by other sites. Please contact the content providers to delete copyright contents if any and email us, we'll remove relevant links or contents immediately.