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Rajiv Shah

DataRobot
Data Scientist
Illinois, USA

Rajiv Shah is a data scientist at a large insurance company and an Adjunct Assistant Professor at the University of Illinois at Chicago. He is an active member of the data science community in Chicago with projects and publications related to surveillance and red light cameras and also has a recent interest in NBA motion tracking data (SportVu). He has a PhD from the University of Illinois at Urbana Champaign.

8:00am PDT

Registration check-in McCaw Hall

9:00am PDT

Handling and analyzing spatial, spatiotemporal and movement data (Part 1) SIEPR 120

10:30am PDT

Handling and analyzing spatial, spatiotemporal and movement data (Part 2) SIEPR 120

1:00pm PDT

Missing Value Imputation with R (Part 1) Barnes

2:30pm PDT

Missing Value Imputation with R (Part 2) Barnes

4:15pm PDT

What's up with the R consortium? McCaw Hall

5:00pm PDT

R-Ladies Presentation 1 McCaw Hall

5:10pm PDT

R-Ladies Presentation 2 McCaw Hall

9:00am PDT

Forty years of S McCaw Hall

10:30am PDT

R in machine learning competitions McCaw Hall

11:06am PDT

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

11:24am PDT

Fitting complex Bayesian models with R-INLA and MCMC Barnes & McDowell & Cranston

11:42am PDT

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

1:00pm PDT

Linking htmlwidgets with crosstalk and mobservable McCaw Hall

1:18pm PDT

htmlwidgets: Power of JavaScript in R Lane & Lyons & Lodato

1:36pm PDT

Introducing Statistics with intRo SIEPR 130

1:54pm PDT

Modeling Food Policy Decision Analysis with an Interactive Bayesian Network in Shiny SIEPR 120

2:12pm PDT

FiveThirtyEight's data journalism workflow with R McCaw Hall

2:30pm PDT

Integrating R & Tableau Sponsor Pavilion Visualizations and Machine Learning in R with Tessera and Shiny Sponsor Pavilion

4:45pm PDT

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

Rectools: An Advanced Recommender System SIEPR 130

9:00am PDT

Towards a grammar of interactive graphics 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

11:15am PDT

Building a High Availability REST API Engine for R SIEPR 120

11:24am PDT

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

11:42am PDT

Classifying Murderers in Imbalanced Data Using randomForest McCaw Hall

10:30am PDT

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

11:25am PDT

Outlier Detection Methods Econ 140

11:40am PDT

rfmt - A new formatter for R source code Econ 140

11:42am PDT

Most Likely Transformations McCaw Hall

1:15pm PDT

Getting R into your bathroom McCaw Hall

1:35pm PDT

Interact with Python from within R McCaw Hall

1:45pm PDT

Optimizing Food Inspections with Analytics McCaw Hall