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2018-n9-brew-and-view

Come join us for the first ever R-themed Brew and View! We are going to curate a few of our favorite talks into 20 minute clips, and then highlight key points and discuss afterward.

2018.erum.io

Homepage of the 2018 event

aboutme

app-consumer-loan

awesome-gbms

A curated list of gradient boosting machines (GBM) resources

benchm-databases

A minimal benchmark of various tools (statistical software, databases etc.) for working with tabular data of moderately large sizes (interactive data analysis).

benchm-dl

Playing with various deep learning tools and network architectures

benchm-dplyr-dt

benchm-ml

A minimal benchmark for scalability, speed and accuracy of commonly used open source implementations (R packages, Python scikit-learn, H2O, xgboost, Spark MLlib etc.) of the top machine learning algorithms for binary classification (random forests, gradient boosted trees, deep neural networks etc.).

benchm-ml--data

Data for benchm-ml, gbm-perf etc. (samples from the airline dataset)

benchm-ml-talks

benchm-r-mysql

bigdatadayla2015-datascience

List of talks from the Data Science Track of Big Data Day LA 2015 (annual free conference)

bio

Szilard Pafka's short bio (to go with conference talk abstracts)

datascience-1slide

Data Science in 1 Slide

datascience-course-historical

Inspired by David Donoho's "50 Years of Data Science" (2015) paper, I'm releasing here a course proposal draft I wrote in 2009 for a possible course of "data science".

datascience-latency

Latency numbers every data scientist should know (aka the pyramid of analytical tasks) - the order of magnitude of computational time for the most common analytical tasks (SQL-like data munging, linear and non-linear supervised learning etc.) with the typically available tools on commodity hardware.

dataset-sizes-kdnuggets

Size of datasets used for analytics based on 10 years of surveys by KDnuggets.

dplyr

Plyr specialised for data frames: faster & with remote datastores

ds_meetups

Contents from the Real Data Science USA (formerly LA Data Science) Meetup

dscomp-winstab

Winner stability in data science competitions

erum2020program

e-Rum2020 program and materials

event-bigdatacampla2014

gbm-adv-workshop-bp19

Advanced GBM Workshop - Budapest, Nov 2019

gbm-intro

GBM intro talk (with R and Python code)

gbm-meltdown

The Effect of the Linux Kernel Page-Table Isolation (KPTI) Patch (Meltdown Vulnerability) on GBMs

gbm-multicore

GBM multicore scaling: h2o, xgboost and lightgbm on multicore and multi-socket systems

gbm-perf

Performance of various open source GBM implementations

gbm-tune

Tuning GBMs (hyperparameter tuning) and impact on out-of-sample predictions

gbm-workshop

Code (and other materials) for an introductory talk/workshop on GBMs (developed originally for an R-Ladies Meetup)