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Alex Cozzi

eBay Inc.
Applied Researcher
San Francisco Bay Area

R user, Scala programmer. Interested in large scala human-computer interaction

8:00am PDT

Registration check-in McCaw Hall

9:00am PDT

Never Tell Me the Odds! Machine Learning with Class Imbalances (Part 1) Econ 140 Time-to-Event Modeling as the Foundation of Multi-Channel Revenue Attribution (Part 1) Barnes

10:30am PDT

Never Tell Me the Odds! Machine Learning with Class Imbalances (Part 2) Econ 140

12:00pm PDT

Lunch Lyons & Lodato

1:00pm PDT

An Introduction to Bayesian Inference using R Interfaces to Stan (Part 1) SIEPR 130 Introduction to SparkR (Part 1) Econ 140

2:30pm PDT

An Introduction to Bayesian Inference using R Interfaces to Stan (Part 2) SIEPR 130

8:30am PDT

Opening Session McCaw Hall

9:00am PDT

Forty years of S McCaw Hall

10:00am PDT

Coffee Break with Poster Exhibits McCaw Hall

10:30am PDT

bamdit: An R Package for Bayesian meta-analysis of diagnostic test data Barnes & McDowell & Cranston edeaR: Extracting knowledge from process data Econ 140

10:48am PDT

Two-sample testing in high dimensions Lane & Lyons & Lodato

11:06am PDT

Bayesian analysis of generalized linear mixed models with JAGS Barnes & McDowell & Cranston

11:42am PDT

bayesboot: An R package for easy Bayesian bootstrapping Barnes & McDowell & Cranston

12:00pm PDT

Lunch with Poster Exhibits Sponsor Pavilion

1:00pm PDT

Group and sparse group partial least squares approaches applied in a genomics context Barnes & McDowell & Cranston

2:12pm PDT

FiveThirtyEight's data journalism workflow with R McCaw Hall

3:30pm PDT

Literate Programming McCaw Hall

9:00am PDT

Towards a grammar of interactive graphics McCaw Hall

10:00am PDT

Coffee Break with Poster Exhibits McCaw Hall

10:30am PDT

Importing modern data into R SIEPR 130

10:48am PDT

Size of Datasets for Analytics and Implications for R Econ 140

11:24am PDT

Heatmaps in R: Overview and best practices Barnes & McDowell & Cranston

11:40am PDT

Chunked, dplyr for large text files SIEPR 120

12:00pm PDT

Lunch with Poster Exhibits McCaw Hall

1:00pm PDT

R at Google Lane & Lyons & Lodato

1:18pm PDT

How to use the archivist package to boost reproducibility of your research Barnes & McDowell & Cranston

2:30pm PDT

Data Quality Profiling - The First Step with New Data Sponsor Pavilion hurdlr: An R package for zero-inflated and over-dispersed count data Sponsor Pavilion

3:30pm PDT

Flexible and Interpretable Regression Using Convex Penalties McCaw Hall

9:00am PDT

Statistical Thinking in a Data Science Course McCaw Hall

10:30am PDT

Gradient Boosted Trees Model: deploying R models into production environments* Lane & Lyons & Lodato