Posted by **FenixN** at Jan. 9, 2017

HDRips | MP4/AVC, ~461 kb/s | 1280x720 | Duration: 03:46:46 | English: AAC, 128 kb/s (2 ch) | 922 MB

Practice and apply R programming concepts for effective statistical and data analysis

Posted by **FenixN** at Nov. 17, 2016

HDRips | MP4/AVC, ~528 kb/s | 1280x720 | Duration: 05:12:40 | English: AAC, 128 kb/s (2 ch) | 1.4 GB

Build R packages, gain in-depth knowledge of machine learning, and master advanced programming techniques in R.

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 **FenixN** at Sept. 20, 2016

HDRips | MP4/AVC, ~447 kb/s | 1920x1080 | Duration: 03:06:17 | English: AAC, 235 kb/s (2 ch) | 959 MB

The R programming language is widely used in statistical programming and is rapidly becoming the language of choice for scientists working with big data. Get a fast start on R and the tools for using it in this introductory video from Dwight Goins.

Posted by **house23** at Jan. 27, 2015

MP4 | AVC 108kbps | English | 960x540 | 29.97fps | 11 hours | AAC stereo 128kbps | 910 MB

This course introduces concepts, languages, techniques, and patterns for programming heterogeneous, massively parallel processors. Its contents and structure have been significantly revised based on the experience gained from its initial offering in 2012. It covers heterogeneous computing architectures, data-parallel programming models, techniques for memory bandwidth management, and parallel algorithm patterns.

Posted by **AlenMiler** at Dec. 29, 2016

English | 31 Jan. 2017 | ISBN: 1491950781 | 222 Pages | AZW3/MOBI/EPUB/PDF (conv) | 8.59 MB

There are many excellent R resources for visualization, data science, and package development. Hundreds of scattered vignettes, web pages, and forums explain how to use R in particular domains.

Posted by **house23** at Nov. 10, 2016

MP4 | AVC 928kbps | English | 1280x720 | 30fps | 11h 42mins | AAC stereo 60kbps | 3.79 GB

Learn to program statistical applications and Monte Carlo simulations with numerous "real-life" cases and R software.

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. 11, 2016

MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 3.5 Hours | Lec: 45 | 434 MB

Graphs with R analytic tool

Posted by **AlenMiler** at Sept. 16, 2016

English | 21 Jun. 2016 | ISBN: 1534798161 | 212 Pages | AZW3/MOBI/EPUB/PDF (conv) | 16.75 MB

R is a language and programming environment for statistical analysis and graphic. It is a project of free software , a result of the implementation GNU classic scientific language S-plus.