I'm an Assoc. Prof. of Math at Queens College (NYC) where I run the undergrad Data Science major, my PhD is in Statistics, my research is in experimental design
bartMachine. An R-Java Bayesian Additive Regression Trees implementation
65ICEbox. An R package for better visualizing a statistical learning model
35Wharton_Stat_422_722. The official class webpage for Statistics 422/722 taught at Wharton in the Spring of 2017
17QC_MATH_342W_Spring_2021. Course Homepage for Math 342W Intro to Data Science and Machine Learning at Queens College
9QC_Math_241_Fall_2017. This is the homepage for Fall 2017's Math 241 taught at Queens College by Professor Adam Kapelner
8QC_MATH_342W_Spring_2024. Course Homepage for Math 342W / 642 / RM 742 Fundamentals of Data Science at Queens College
7GemIdent. An image segmentation platform using Statistical Learning developed by Professor Susan Holmes and Adam Kapelner, under GPL2.
6QC_MATH_342W_Spring_2022. Course Homepage for Math 342W Intro to Data Science and Machine Learning at Queens College
6QC_Math_621_Fall_2019. Homepage for Fall 2019's intermediate probability class (Math 621) taught at Queens College by Professor Adam Kapelner
5QC_MATH_340_Fall_2023. Course Homepage for Math 340 / 640 Probability Theory for Data Science and Statistics at Queens College
5QC_Math_390.03-02_Spr_2016. Course homepage for Bayesian Modeling (Math 390.03-02) for the Spring, 2016 semester at Queens College, CUNY
5QC_Math_621_Fall_2020. TeX
5QC_Math_390.4_Spring_2019. Course Homepage for Math 390.4 Intro to Data Science and Machine Learning at Queens College in the Spring, 2019
4QC_Math_369_Fall_2020. TeX
4QC_MATH_342W_Spring_2025. TeX
4QC_Math_390.4_Spring_2018. Course Homepage for Math 390.4 Intro to Data Science and Machine Learning at Queens College in the Spring, 2018
4QC_Math_341_Spring_2019. The course homepage for Math 341 (and Masters level 650.3-02) for the Spring semester, 2019 at Queens College, City University of New York
3QC_MATH_341_Fall_2024. Course homepage for Math 341 / 641 at Queens College, CUNY
3QC_Math_390.4_Spring_2020. Course Homepage for Math 390.4 Intro to Data Science and Machine Learning at Queens College in the Spring, 2020
3QC_Math_241_Fall_2016. Math 241 course homepage for the Fall 2016 semester at Queens College
3QC_MATH_241_Fall_2021. The course homepage for Math 241 Fall 2021
3QC_Math_341_Spring_2021. TeX
2QC_Math_241_Fall_2015. Math 241 course homepage for the Fall 2015 semester at Queens College
2QC_MATH_341_Fall_2025. Course homepage for Math 341 / 641 at Queens College, CUNY
2QC_Math_341_Spring_2018. TeX
2QC_MATH_343_Spring_2025. About Course Homepage for Math 343 Computational Statistics for Data Science at Queens College
2QC_Math_341_Spring_2017. Course Homepage for Math 341 Bayesian Modeling at Queens College in the Spring, 2017
2QC_Math_341_Spring_2020. The course homepage for Math 341 (and Masters level 650.3) for the Spring semester, 2020 at Queens College, City University of New York
2QC_MATH_340_Fall_2024. Course homepage for Math 340 / 640 at Queens College, CUNY
2QC_Math_241_Spring_2015. Math 241 course homepage for the Spring 2015 semester at Queens College
1fastLogisticRegressionWrap. The public repository for the R package fastLogisticRegressionWrap on CRAN
1QC_MATH_343_Spring_2024. Course Homepage for Math 343 Computational Statistics for Data Science at Queens College
1QC_MATH_341_Fall_2023. Course Homepage for Math 341 / 641 Statistical Theory for Data Science at Queens College
1QC_MATH_340_Fall_2025. Course homepage for Math 340 / 640 at Queens College, CUNY
1YARF. Yet Another Random Forests [Implementation]
1QC_Math_241_Fall_2014_15. Course homepage for Math 241 for Fall 2014-15 at Queens College
1CovBalAndRandExpDesign. This is the home of the source code for R package "CovBalAndRandExpDesign".
1PTE. Personalized Treatment Evaluator
1breaking_monotony. Code and supplementary materials for the publication "Breaking Monotony with Meaning: Motivation in Crowdsourcing Markets"
1Stat101_Summer_2011. The course materials for my summer 2011 class in basic Statistics for undergraduates.
1GemVident. An video particle tracking program developed by Adam Kapelner, Adam Guetz, and Professor Susan Holmes. It is a natural extension of GemIdent, a statistical-learning based image segmentation platform.
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