Pinned Repositories
burcukolcak.github.io
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
Causal-Inference-1
Causal Inference 1 Mixtape Session
DataScienceCourse
This holds iPython notebooks and lecture slides for the Intro to Data Science Master's course I teach at NYU.
hate-speech-and-offensive-language
Repository for the paper "Automated Hate Speech Detection and the Problem of Offensive Language", ICWSM 2017
presidential-documents-scraping
Scraping Presidential Documents from the Web
quanteda
An R package for the Quantitative Analysis of Textual Data
r-workshop-spring2021
Introduction to R Workshop for Polisci Graduate Students, Rutgers University, Spring 2021
stat_rethinking_2022
Statistical Rethinking course winter 2022
tad_19
Text as Data 2019
text-as-data-class-spring2021
Lectures and "flipped session" materials from my NYU DS "Text as Data" course, spring 2021
burcukolcak's Repositories
burcukolcak/presidential-documents-scraping
Scraping Presidential Documents from the Web
burcukolcak/burcukolcak.github.io
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
burcukolcak/Causal-Inference-1
Causal Inference 1 Mixtape Session
burcukolcak/DataScienceCourse
This holds iPython notebooks and lecture slides for the Intro to Data Science Master's course I teach at NYU.
burcukolcak/hate-speech-and-offensive-language
Repository for the paper "Automated Hate Speech Detection and the Problem of Offensive Language", ICWSM 2017
burcukolcak/quanteda
An R package for the Quantitative Analysis of Textual Data
burcukolcak/r-workshop-spring2021
Introduction to R Workshop for Polisci Graduate Students, Rutgers University, Spring 2021
burcukolcak/stat_rethinking_2022
Statistical Rethinking course winter 2022
burcukolcak/tad_19
Text as Data 2019
burcukolcak/text-as-data-class-spring2021
Lectures and "flipped session" materials from my NYU DS "Text as Data" course, spring 2021
burcukolcak/tensorflow
An Open Source Machine Learning Framework for Everyone