olegdanilchenko's repositories
socialRinsight
Tools for the analytics professional to scrape data from social media APIs like Facebook and Twitter
AdvancedAnalyticsRCIS
Обучению материалы для изучения основных методик Advanced Analytics
AutomatedForecastingWithShiny
Fully automated GDP forecasting with R/shiny
ChurnAnalysisUsingR
This project demonstrates churn analysis for telecom industries. Mobile carriers are first priority to monetize rich supplies of customer information—while being mindful of legal and privacy issues. When data assets are transformed into new revenue streams, next-generation analytics will become integral to high performance. The aim of churn analysis is to identify customers who are about to transfer their business to a competitor.
courses
Course materials for the Data Science Specialization: https://www.coursera.org/specialization/jhudatascience/1
Customer-Data-Analytics
A brief Project displaying an array of data science skills
datasciencecoursera
Cousera's Data Scientists course data
datasharing
The Leek group guide to data sharing
esa_data_viz
ESA 2013, Data Visualization in R workshop
googleVis
Interface between R and the Google Chart Tools
Mining_Twitter_feeds_with_R
Mining Twitter feeds with R - Case example MH370 tragedy
ml-class
The assignment code of machine leaning course by ng on the coursera^-^
networkD3
Tools for creating D3 JavaScript network graphs from R
R_Workshop
R programming workshop
radiant
Business analytics using R and Shiny
Rapidminer
Code files for my books on Rapidminer
rCharts
Interactive JS Charts from R
rChartsShiny
Interactive Visualizations with rCharts and Shiny
Rfacebook-1
Access to Facebook API via R
shiny
Easy interactive web applications with R
shiny-apps
R Shiny apps
ShinyBuilder
Visual dashboard builder platform based on R/Shiny
trelliscope
Detailed Visualization of Large Complex Data in R
webinars
Code and slides for RStudio webinars
Wiley-ADCR
Repository for the book "Automated Data Collection with R"
zmPDSwR
Example R scripts and data for "Practical Data Science with R" by Nina Zumel and John Mount (Manning Publications)