The global.R file What does it do? How do you do it? Final thought The global.R file Anybody who has ever created a shiny app or a shinydashboard has probably had the problem of the ui.R and server.R or the app.R files becoming very complex and crowded. Sure, if you’re app is very simple, you don’t have any side-bar with several tabs, etc. then you probably don’t know what I’m talking about, but bear with me, this might still be interesting further down the road on your journey to becoming a Shiny master.
Getting started Set up I bought Chollet and Allaire’s insanely good Deep Learning with R book and wanted to follow along with the example Neural Networks in R with Keras. However, my machine does not have a GPU that is powerful enough, let alone have CUDA capabilities 🙄. Thus I set forth, as the authors suggest, to create an AWS EC2 instance. Since there can be many tiny obstacles to prevent you from having a smooth start, I wrote this post, so you can get a timely start on your deep learning endeavors.
Bayesian Inference im Kino Wahrscheinlichkeit Verbundwahrscheinlichkeit (joint probability) Randwahrscheinlichkeit (marginal probability) Bayes’ Theorem Wahrscheinlichkeitsverteilung (probability distributions) Bayesian Inference beim Tierarzt Bayes-Fallen vermeiden This is my translation of Brandon Rohrer’s blog post (Nov 2, 2016) and utterly awesome explanation of Bayesian Inference. https://www.youtube.com/watch?v=5NMxiOGL39M&feature=youtu.be Bayesian Inference kann genutzt werden um genauere Vorhersagen über einen Datensatz zu erhalten. Die Technik ist besonders dann nützlich, wenn man nicht so viele Daten hast, wie man gerne hätte - deshalb will man so viel wie möglich an Vorhersagegenauigkeit aus ihnen herausquetschen.