A short note on information-theoretic variable screening in R w. {information}. Variable screening comes as an important step in the contemporary EDA for predictive modeling: what can we tell about the nature of the relationships between a set of predictors and the dependent before entering the modeling phase? Can we ... [Read more...]

The visualization of complex data sets is of essential importance in communicating your data products. Beyond pie charts, histograms, line graphs and other common forms of visual communication begins the reign of data sets that encompass too much information to be easily captured by these simple data displays. A typical ... [Read more...]

In this continuation of “Hybrid content-based and collaborative filtering recommendations with {ordinal} logistic regression (1): Feature engineering” I will describe the application of the {ordinal} clm() function to test a new, hybrid content-based, collaborative filtering approach to recommender engines by fitting a class of ordinal logistic (aka ordered logit) models to ... [Read more...]

I will use {ordinal} clm() (and other cool R packages such as {text2vec} as well) here to develop a hybrid content-based, collaborative filtering, and (obivously) model-based approach to solve the recommendation problem on the MovieLens 100K dataset in R. All R code used in this project can be obtained ... [Read more...]

This post was originally published on SmartCat, 22 Feb 2017.My inaugural blog as a Data Science Consultant for SmartCat. The code that accompanies the analyses presented here is available at the respective GitHub repository. On how to use R to estimate the optimal time during the day for aliens to invade ... [Read more...]

The notebooks (R, Rmd, and HTML files are provided in my GitHub repository) focus on an exploratory analysis of the open data set on the complaints in the field of freedom of information, provided at the Open Data Portal of the Republic of Serbia that is currently under development. The ... [Read more...]

The R code that accompanies this post is found on GitHub: you will find R, Rmd, and HTML files there that were used during the first Open Data R Meetup held in Belgrade, 31 January 2017, organized by Data Science Serbia in Startit Center, Savska 5, Bel... [Read more...]

The R code for this tutorial on Methods of Distributional Semantics in R is found in the respective GitHub repository. You will find .R, .Rmd, and .html files corresponding to each part of this tutorial (e.g. DistSemanticsBelgradeR-Part2.R, DistSemant... [Read more...]

The R code for this tutorial on Methods of Distributional Semantics in R is found in the respective GitHub repository. Following my Methods of Distributional Semantics in R BelgradeR Meetup with Data Science Serbia, organized in Startit Center, Belgrade, 11/30/2016, several people asked me for the R code used for the ... [Read more...]

Welcome to Introduction to R for Data Science, Session 8: Intro to Text Mining in R, ML Estimation + Binomial Logistic Regression [Web-scraping with tm.plugin.webmining. The tm package corpora structures: assessing document metadata and content. Typical corpus transformations and Term-Document Matrix production. A simple binomial regression model with tf-idf scores ... [Read more...]

Appendix to Session 8: Intro to Text Mining in R, ML Estimation + Binomial Logistic RegressionWelcome to Introduction to R for Data Science, Session 8: Intro to Text Mining in R, ML Estimation + Binomial Logistic Regression [Web-scraping with tm.plugin.webmining. The tm package corpora structures: assessing document metadata and content. Typical corpus ... [Read more...]

Welcome to Introduction to R for Data Science Session 7: Multiple Regression + Dummy Coding, Partial and Part Correlations [Multiple Linear Regression in R. Dummy coding: various ways to do it in R. Factors. Inspecting the multiple regression model: regression coefficients and their interpretation, confidence intervals, predictions. Introducing {lattice} plots + ggplot2. Assumptions: ... [Read more...]

Welcome to Introduction to R for Data Science Session 6: Linear Regression + EDA, and Normality tests [Linear Regression in R: Exploratory Data Analysis, assumptions of the simple linear model, correlation, and visualization. Predictions from the linear model. Confidence Intervals and Residuals. Inspecting the basic linear model. Infulential cases and the Influence ... [Read more...]

Welcome to Introduction to R for Data Science Session 5: Structuring Data: String manipulation in R. [Strings in R: {base}, {stringr}, and {stringi} packages. String concatenation, splitting, subsetting, and transformation. On encodings in R.] The course is co-organized by Data Science Serbia and Startit. You will find all course material (R ... [Read more...]

Welcome to Introduction to R for Data Science Session 4! The course is co-organized by Data Science Serbia and Startit. You will find all course material (R scripts, data sets, SlideShare presentations, readings) on these pages. Welcome to the fourth session of Introduction to R for Data Science! Check out the ... [Read more...]

Welcome to Introduction to R for Data Science Session 3! The course is co-organized by Data Science Serbia and Startit. You will find all course material (R scripts, data sets, SlideShare presentations, readings) on these pages. Welcome to the third session of Introduction to R for Data Science! Check out the ... [Read more...]

Welcome to Introduction to R for Data Science Session 2! The course is co-organized by Data Science Serbia and Startit. You will find all course material (R scripts, data sets, SlideShare presentations, readings) on these pages. [in Serbian] Lecturers dipl. ing Branko Kovač, Data Analyst at CUBE, Data Science Mentor at ... [Read more...]

Branko Kovač Data Analyst at CUBE, Data Science Mentor at Springboard, Institut savremenih nauka, Data Science Serbia, and Goran S. Milovanović, DataScientist@DiploFoundation, Data Science Serbia, are giving a free introductory course on R for Data Science in Belgrade, Serbia. All course materials - slides, R scripts, data sets, summaries ... [Read more...]

Welcome to Introduction to R for Data Science Session 1! The course is co-organized by Data Science Serbia and Startit. You will find all course material (R scripts, data sets, SlideShare presentations, readings) on these pages. [in Serbian] Lecturers dipl. ing Branko Kovač, Data Analyst at CUBE, Data Science Mentor at ... [Read more...]