This month we have Alan Dipert from RStudio coming to talk about integrating React.js and Shiny. Alan is one of the key developers behind the development of Shiny and we are so lucky to have him there to share his knowledge. The Paul Merage School of Business at UCI is graduating their second cohort of students from their MS in Business Analytics program. Last year we invited them to present their Capstone projects and it was a huge success, so they are back this year.
These talks will be held on Monday, April 29th, 2019. #=== Talks Speaker: Ash Pahwa Title: Deep Learning using R and TensorFlow (Part 2) Abstract: Google released TensorFlow software in 2015 targeted for the Deep Learning applications. Two primary misconceptions about TensorFlow are as follows. First, it can only be used with Python and second, it can only be used for building deep learning applications This talk will demystify these concepts.
These talks will be held on Tuesday, March 26th, 2019. TensorFlow has become the defacto standard for distributed computing of deep neural networks. For over a year, R has had excellent support for this capability via a series of interrelated packages (keras, tfestimators, tensorflow, tfdatasets). Check out https://tensorflow.rstudio.com/ Then come join us for the first part of a two-part talk on using R and TensorFlow. Hadley Wickham famously said, “it’s not that we don’t test our code, it’s that we don’t store our tests so they can be re-run automatically.
These talks will be held on Tuesday, February 26th, 2019. #=== Talks Speaker: Yemi Odeyemi Title: Opinion Mining of Climate Change Research Climate is defined as the long-term impact of weather on a specific locality. Statistically, climate is defined as the average weather for a specific area over a defined period, usually over three to four decades. Over the years we have seen the socioeconomic impacts of climate change on public health, agriculture/nutrition, nutrient cycle, migration, local economy.
These talks will be given on January 29, 2019. ==== Talks Speaker: Ryan Benz Title: Tibbles, and list columns, and nested data frames, oh my! Tibbles are a “modern reimagining of the data.frame” and are a big part of the tidyverse, but what are they really, how are they different from standard data frames, any why should you care about using them? In this talk, I’ll dive into tibbles and show how they can be used in several interesting ways taking advantage of list columns and nested data frames.