Posted by **BUGSY** at Aug. 31, 2015

English | Jan. 2, 2013 | ISBN: 1441977864, 1461427495 | 662 Pages | PDF | 11 MB

Financial engineers have access to enormous quantities of data but need powerful methods for extracting quantitative information, particularly about volatility and risks. Key features of this textbook are: illustration of concepts with financial markets and economic data, R Labs with real-data exercises…

Posted by **FenixN** at Nov. 24, 2016

HDRips | MP4/AVC, ~107 kb/s | 1280x720 | Duration: 01:39:07 | English: AAC, 128 kb/s (2 ch) | 224 MB

Unleash the powerful capabilities of R to work effectively with data.

Posted by **FenixN** at Nov. 20, 2016

HDRips | MP4/AVC, ~499 kb/s | 1280x720 | Duration: 15:14:52 | English: AAC, 128 kb/s (2 ch) | 3.53 GB

Learn R and get comfortable with data science.

Posted by **FenixN** at Nov. 16, 2016

HDRips | MP4/AVC, ~1500 kb/s | 960x528 | Duration: 15:12:01 | English: AAC, 128 kb/s (2 ch) | 5,46 GB

R Programming Data Analyst Learning Path, is a tour through the most important parts of R, the statistical programming language, from the very basics to complex modeling. It covers reading data, programming basics, visualization, data munging, regression, classification, clustering, modern machine learning, network analysis, web graphics, and techniques for dealing with large data, both in memory and in databases.

Posted by **Underaglassmoon** at Nov. 15, 2016

Apress | Computer Science | December 2, 2016 | ISBN-10: 1484222970 | 261 pages | pdf | 21.54 mb

Authors: Beard, Bradley

Appeals to data scientists and quantitative analysts who rely upon R for analyzing data and driving business decisions

Provides examples in SQL Server R Services, and in R Tools for Visual Studio

Posted by **ParRus** at Nov. 10, 2016

WEBRip | English | MP4 | 1280 x 720 | AVC ~936 kbps | 30 fps

AAC | 61.9 Kbps | 44.1 KHz | 2 channels | 05:52:02 | 2.39 GB

Use the R Programming Language to execute data science projects and become a data scientist. Implement business solutions, using machine learning and predictive analytics. The R language provides a way to tackle day-to-day data science tasks, and this course will teach you how to apply the R programming language and useful statistical techniques to everyday business situations. With this course, you'll be able to use the visualizations, statistical models, and data manipulation tools that modern data scientists rely upon daily to recognize trends and suggest courses of action.

Posted by **FenixN** at Nov. 9, 2016

HDRips | MP4/AVC, ~421 kb/s | 1280x720 | Duration: 05:32:47 | English: AAC, 128 kb/s (2 ch) | 1.67 GB

Over 100 hands-on tasks to help you effectively solve real-world data problems using the most popular R packages and techniques

Posted by **FenixN** at Nov. 6, 2016

HDRips | MP4/AVC, ~84 kb/s | 1280x720 | Duration: 02:17:02 | English: AAC, 128 kb/s (2 ch) | 335 MB

A complete course to help you learn all the relevant aspects of data mining using R.

Posted by **house23** at Nov. 5, 2016

MP4 | AVC 470kbps | English | 1280x720 | 30fps | 17 hours | AAC stereo 59kbps | 2.68 GB

This course ensure quick learning in a simplified way. It explains the most important aspects of working on data and conduct analysis through example. You will start by learning how to install and navigate R studio. Learn Data/Object Types and Operations, Importing into R, and Loops and Conditions. you will be introduced to the use of R in Analytics, where you will learn a little about each object type in R and use that in Data Mining/Analytical Operations. learn the use of R in Statistics, using R to evaluate Descriptive Statistics, Probability Distributions, Hypothesis Testing, Linear Modeling, Generalized Linear Models, Non-Linear Regression, and Trees. Learn to create 2-dimensional Univariate and Multi-variate plots.

Posted by **naag** at Oct. 30, 2016

MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 2.5 Hours | 418 MB

Data science is becoming more and more valuable to the workplace and to the global economy. Learn how to use the practice of data science and the programming language R to transform your data into actionable insight.