Publications by The Exactness of Mind
Distributional Semantics in R: Part 1 {tm} classes + read/write
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 analysis of William Shakesp...
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Distributional Semantics in R: Part 2 Entity Recognition w. {openNLP}
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, DistSemanticsBelgradeR-Part2.Rmd, and DistSemanticsBelgradeR-Part2.html, for Part 2) there. All auxiliary...
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Open Data R Meetup: exploring the Distribution of Traffic Accidents in Belgrade, 2015 in R
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, Belgrade Serbia. The Open Data initiative in Serbia is still young, our Open Data Portal is still u...
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R in Open Data: Complaints in The Field of Freedom of Information data set from data.gov.rs
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 data set was kindly provided to the Open Data Portal by the...
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#AskNASA: What’s the Optimal Time for Aliens to Invade Earth?
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 Earth and a few more interesting things.A ...
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Hybrid content-based and collaborative filtering recommendations with {ordinal} logistic regression (1): Feature engineering
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 from the respective GitHub repository; t...
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Hybrid content-based and collaborative filtering recommendations with {ordinal} logistic regression (2): Recommendation as discrete choice
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 log...
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Visualising Similarity: Maps vs. Graphs
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 context that abounds ...
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WoE and IV Variable Screening with {Information} in R
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 infer something about the p...
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