Deep Learning using R, REST APIs and Shiny
Details
NOTE: THE DATE HAS CHANGED TO MONDAY APRIL 29, 6:30 PM
#=== 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. First, TensorFlow can also be used with R and any programming language. Second, TensorFlow’s main objective is to solve the mathematical problem (including differential equations) which contains multi-dimensional arrays (or tensors). Deep Learning Neural Networks is just another application of TensorFlow.
In this second part, neural networks optimization techniques will be discussed. The implementation of Gradient Descent and Adam (Adaptive Momentum Estimation) optimization techniques will be covered using R and TensorFlow.
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Speaker: Peter Stemler
Title: REST APIs and Shiny
A brief show and tell of how you can use R to pull data from multiple business softwares into a Shiny app.
