rstatsnyc as told by @brookLYNevery1, @dataandme, and autographs

An ongoing set up updates about what happened at the 2018 NYC R Conference

By Daniel Chen

April 22, 2018

EDIT: I’ve added the notes from @dataandme and linked to people’s twitter and slides (if I found them). This is probably going to be an ongoing process…

Another year and another talk at the NYC R Conference. As always, the conference was filled with excellent speakers (I’m biased here becuase I was one of them…), food, and people.

Brooke Watson ( @brookLYNevery1) did a fantastic job illustrating and summarzing all of the talks. So I’ve just linked to all her tweets (after the break).

Oh… and I got my books signed :)

#rstatsnyc as told by #autographs. #rstats #nycdatamafia #python #datascience

A post shared by Daniel Chen (@chendaniely) on

Accelerating Cancer Research with R

Sandy Griffith, Flatiron Health, @sgrifter

Skin First, Makeup Second: A Metaphor for Data Science

Eurry Kim, Glossier, @eurryPlot

R for Big Data in the Cloud

Marck Vaisman, Microsoft, @wahalulu

The Lesser Known Stars of the Tidyverse

Emily Robinson, DataCamp, @robinson_es

Deep Learning vs Machine Learning in R

Jared P. Lander, Lander Analytics, @jaredlander

Doing Data Science

Dan Chen, Virginia Tech, @chendaniely

slides

First time converting slides to PDF. First time publishing on Speaker Deck. Hope it turns out okay >.<

Forecasting at Scale: How and Why We Developed Prophet for Forecasting at Facebook

Sean Taylor, Facebook, @seanjtaylor

The Modern R Data Package

Noam Ross, ROpenSci & EcoHealth Alliance, @noamross

Open Source Sampling: Building and Remixing Packages in R

Brooke Watson, EcoHealth Alliance, @brookLYNevery1

R in USMA

Dusty Turner, United States Military Academy, @DTDusty

Applying Deep Learning to Satellite Images to Estimate Violence in Syria and Poverty in Mexico

Jonathan Hersh, Chapman University, @DogmaticPrior

Apache Arrow: A Cross-Language Development Platform for In-Memory Analytics

Wes McKinney, Two Sigma, @wesmckinn

slides

R in Minecraft

David Smith, Microsoft, @revodavid

May the R be with You: Exploring the Star Wars Universe

Evelina Gabasova, Alan Turing Institute, @evelgab

Patterns and Drivers of Ice Shelf Melt

Alex Boghosian, Columbia

Cracking into the Meat of R with lobstr: Console Visualisations that Explain How Stuff Works

Hadley Wickham, RStudio, @hadleywickham

Introduction to scikit-learn

Andreas Mueller, Columbia, @amuellerml

slides

How Long Will I Live? The Statistics Behind Prognosis in Cancer Research

Emily Zabor, Memorial Sloan Kettering, @zabormetrics

slides

Automated Versus Do-it-Yourself Methods for Causal Inference: Lessons Learned From a Data Analysis Competition

Jennifer Hill, New York University

Teach the Tidyverse to Beginners

David Robinson, DataCamp, @drob

Open Source Success: A Decade of R in Finance

Jeff Ryan, Citadel, @lemnica

Investigating User Experience with Natural Language Analysis

Stephanie Kim, Algorithmia, @StephLKim

Phrasing: Communicating Data Science Through Tweets, Gifs, and Classic Misdirection

Mara Averick, RStudio, @dataandme

Comparing Posteriors: Estimating Practical Differences Between Models

Max Kuhn, RStudio, @topepos

The What-Where-How-Why of GPU computing with R

Kelly O’Briant, MapD, @kellrstats

It’s always fun getting autographed books!

Posted on:
April 22, 2018
Length:
7 minute read, 1377 words
Tags:
R conference rstatsnyc
See Also:
R Hex Bowtie
Table of Model Results using kable and kableExtra
R or Python, which One to Learn (First)?