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Ryota Suzuki

Ef-prime, Inc.
CEO / Data Analyst
Tokyo, Japan

r.analyticflow.com

In my talk I will introduce R AnalyticFlow ( r.analyticflow.com ), an R-GUI for interactive data analysis. We are developing this software in Ef-prime, Inc. ( www.ef-prime.com ), a company that provides consulting and related services in data analysis. I'm also one of the authors of the package pvclust.

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

Understanding and creating interactive graphics (Part 1) McDowell & Cranston

2:30pm PDT

Understanding and creating interactive graphics (Part 2) McDowell & Cranston

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

8:30am PDT

Opening Session McCaw Hall

9:00am PDT

Forty years of S McCaw Hall

10:30am PDT

R in machine learning competitions McCaw Hall

10:48am PDT

Connecting R to the OpenML project for Open Machine Learning McCaw Hall

11:06am PDT

R: The last line of defense against bad debt Econ 140 Taking R to new heights for scalability and performance SIEPR 130

11:24am PDT

Automating our work away: One consulting firm's experience with KnitR Econ 140 Distributed Computing using parallel, Distributed R, and SparkR SIEPR 130

11:42am PDT

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

1:18pm PDT

Experiences on the Use of R in the Water Sector SIEPR 120 Fast additive quantile regression in R Barnes & McDowell & Cranston htmlwidgets: Power of JavaScript in R Lane & Lyons & Lodato Transforming a museum to be data-driven using R 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

RosettaHUB-Sheets, a programmable, collaborative web-based spreadsheet for R, Python and Spark Lane & Lyons & Lodato

2:30pm PDT

High-performance R with FastR Sponsor Pavilion Integrating R & Tableau Sponsor Pavilion mvarVis: An R package for Visualization of Multivariate Analysis Results Sponsor Pavilion RCAP Designer: An RCloud Package to create Analytical Dashboards Sponsor Pavilion Video Tutorials in Introductory Statistics Instruction Sponsor Pavilion Visualizations and Machine Learning in R with Tessera and Shiny Sponsor Pavilion

3:30pm PDT

Literate Programming McCaw Hall

4:45pm PDT

flexdashboard: Easy interactive dashboards for R Lane & Lyons & Lodato

5:03pm PDT

New Paradigms In Shiny App Development: Designer + Data Scientist Pairing Lane & Lyons & Lodato

5:21pm PDT

Using Shiny modules to build more-complex and more-manageable apps Lane & Lyons & Lodato

5:39pm PDT

R AnalyticFlow 3: Interactive Data Analysis GUI for R Lane & Lyons & Lodato

5:57pm PDT

Visual Pruner: A Shiny app for cohort selection in observational studies Lane & Lyons & Lodato

10:30am PDT

Importing modern data into R SIEPR 130

10:48am PDT

ETL for medium data SIEPR 130 Visualizing Simultaneous Linear Equations, Geometric Vectors, and Least-Squares Regression with the matlib Package for R McCaw Hall

11:42am PDT

Exploring the R / SQL boundary SIEPR 130

1:00pm PDT

R at Google Lane & Lyons & Lodato

1:20pm PDT

How Teradata Aster R Scales Data Science Lane & Lyons & Lodato

1:36pm PDT

Revisiting the Boston data set (Harrison and Rubinfeld, 1978) SIEPR 120

1:40pm PDT

Changing lives with Data Science at Microsoft Lane & Lyons & Lodato

1:55pm PDT

Bringing the Power of R to Citizen Data Scientists Lane & Lyons & Lodato

2:05pm PDT

Making the R community more open Lane & Lyons & Lodato

9:00am PDT

Statistical Thinking in a Data Science Course McCaw Hall

10:00am PDT

Coffee Break w/ Poster Exhibits McCaw Hall

10:30am PDT

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

10:50am PDT

ranger: A fast implementation of random forests for high dimensional data Lane & Lyons & Lodato

11:08am PDT

Superheat: Supervised heatmaps for visualizing complex data Lane & Lyons & Lodato

11:26am PDT

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

11:42am PDT

Using Jupyter notebooks with R in the classroom Barnes & McDowell & Cranston

1:00pm PDT

Catching up with Rstudio Lane & Lyons & Lodato

1:20pm PDT

R for Big Data and Applications: Using R at Oracle Lane & Lyons & Lodato

2:00pm PDT

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

3:00pm PDT

Closing Remarks McCaw Hall