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Jeremy Werner

Allstate
Data Scientist
Menlo Park, CA

Talk to me about cryptocurrencies, Minnesota Vikings, or anything data science related!

8:00am PDT

Registration check-in McCaw Hall

9:00am PDT

Machine Learning Algorithmic Deep Dive (Part 1) Campbell Rehearsal Hall

10:15am PDT

Coffee Break Campbell Rehearsal Hall

10:30am PDT

Machine Learning Algorithmic Deep Dive (Part 2) Campbell Rehearsal Hall

12:00pm PDT

Lunch Campbell Rehearsal Hall

1:00pm PDT

Introduction to SparkR (Part 1) Econ 140

2:15pm PDT

Coffee Break Econ 140

2:30pm PDT

Introduction to SparkR (Part 2) Econ 140

4:00pm PDT

Short Break McCaw Hall

4:15pm PDT

What's up with the R consortium? McCaw Hall

4:40pm PDT

Presentation of the Women in R task force McCaw Hall

5:00pm PDT

R-Ladies Presentation 1 McCaw Hall

5:10pm PDT

R-Ladies Presentation 2 McCaw Hall

5:20pm PDT

Discussion McCaw Hall

8:00am PDT

Registration check-in McCaw Hall

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

Using Spark with Shiny and R Markdown SIEPR 130

10:48am PDT

RcppParallel: A Toolkit for Portable, High-Performance Algorithms SIEPR 130

11:06am PDT

trackeR: Intrastructure for running and cycling data from GPS-enabled tracking devices in R McCaw Hall

11:24am PDT

Distributed Computing using parallel, Distributed R, and SparkR SIEPR 130

11:42am PDT

FlashR: Enable Parallel, Scalable Data Analysis in R SIEPR 130

12:00pm PDT

Lunch with Poster Exhibits Sponsor Pavilion

1:00pm PDT

Linking htmlwidgets with crosstalk and mobservable McCaw Hall

1:36pm PDT

What can R learn from Julia Lane & Lyons & Lodato

1:54pm PDT

Zero-overhead integration of R, JS, Ruby and C/C++ Lane & Lyons & Lodato

2:12pm PDT

FiveThirtyEight's data journalism workflow with R McCaw Hall

2:30pm PDT

Coffee Break w/ Poster Session McCaw Hall Urban Mobility Modeling using R and Big Data from Mobile Phones Sponsor Pavilion

3:30pm PDT

Literate Programming McCaw Hall

4:30pm PDT

Short Break McCaw Hall

4:45pm PDT

Covr: Bringing Code Coverage to R Econ 140 mlrMBO: A Toolbox for Model-Based Optimization of Expensive Black-Box Functions SIEPR 130

5:03pm PDT

Deep Learning for R with MXNet SIEPR 130

5:21pm PDT

Interactive Naive Bayes using Shiny: Text Retrieval, Classification, Quantification SIEPR 130

5:39pm PDT

xgboost: An R package for Fast and Accurate Gradient Boosting SIEPR 130

5:57pm PDT

Colour schemes in data visualisation: Bias and Precision McCaw Hall Rectools: An Advanced Recommender System SIEPR 130

6:30pm PDT

Welcome Reception Bing Concert Hall

8:00am PDT

Registration check-in 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

Empowering Business Users with Shiny SIEPR 120

10:48am PDT

Size of Datasets for Analytics and Implications for R Econ 140

11:06am PDT

Calculation and economic evaluation of acceptance sampling plans Barnes & McDowell & Cranston

11:24am PDT

Grid Computing in R with Easy Scalability Econ 140

11:42am PDT

Classifying Murderers in Imbalanced Data Using randomForest McCaw Hall

12:00pm PDT

Lunch with Poster Exhibits McCaw Hall

1:00pm PDT

A spatial policy tool for cycling potential in England SIEPR 120 R markdown: Lifesaver or death trap? McCaw Hall

1:18pm PDT

SpatialProbit for fast and accurate spatial probit estimations SIEPR 120

1:36pm PDT

Adding R, Jupyter and Spark to the toolset for understanding the complex computing systems at CERN's Large Hadron Collider McCaw Hall Revisiting the Boston data set (Harrison and Rubinfeld, 1978) SIEPR 120

1:54pm PDT

How to do one's taxes with R McCaw Hall Spatial data in R: simple features and future perspectives SIEPR 120

2:12pm PDT

High performance climate downscaling in R SIEPR 120

2:30pm PDT

Coffee Break with Poster Session McCaw Hall Logistic modelling of increased antibacterial resistance with sales Sponsor Pavilion

3:30pm PDT

Flexible and Interpretable Regression Using Convex Penalties McCaw Hall

4:30pm PDT

Cruise & Conference Dinner 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

10:48am PDT

Practical tools for exploratory web graphics SIEPR 130

11:06am PDT

Estimation of causal effects in network-dependent data McCaw Hall

11:26am PDT

Big data algorithms for rank-based estimation Lane & Lyons & Lodato

11:42am PDT

Most Likely Transformations McCaw Hall

12:00pm PDT

Lunch w/ Poster Exhibits McCaw Hall

1:00pm PDT

Hash Tables in R are Slow SIEPR 130

1:15pm PDT

Getting R into your bathroom McCaw Hall

1:30pm PDT

The Best Time to Post on Reddit McCaw Hall

1:35pm PDT

Scalable Machine Learning in R with H2O Lane & Lyons & Lodato

2:00pm PDT

RCloud - Collaborative Environment for Visualization and Big Data Analytics McCaw Hall

3:00pm PDT

Closing Remarks McCaw Hall