Shiny Dev Center gets a shiny new update

I am excited to announce the redesign and reorganization of shiny.rstudio.com, also known as the Shiny Dev Center. The Shiny Dev Center is the place to go to learn about all things Shiny and to keep up to date with it as it evolves.


Kernels Part 1: What is an RBF Kernel? Really?

My first blog on machine learning is to discuss a pet peeve I have about working in the industry, namely why not to apply an RBF kernel to text classification tasks.


An Intuitive Guide to Deep Network Architectures

Over the past few years, much of the progress in deep learning for computer vision can be boiled down to just a handful of neural network architectures. Setting aside all the math, the code, and the implementation details, I wanted to explore one simple question: how and why do these models work?


Packages to simplify mapping in R

Computerworld’s Sharon Machlis has published a very useful tutorial on creating geographic data maps with R. (The tutorial was actually published back in March, but I only came across it recently.) While it’s been possible to create maps in R for a long time, some recent packages and data APIs have made the process much simpler.


Neat New seplyr Feature: String Interpolation

The R package seplyr has a neat new feature: the function seplyr::expand_expr() which implements what we call “the string algebra” or string expression interpolation. The function takes an expression of mixed terms, including: variables referring to names, quoted strings, and general expression terms. It then “de-quotes” all of the variables referring to quoted strings and “dereferences” variables thought to be referring to names. The entire expression is then returned as a single string.


Einstein Platform: Fuel for AI-enabled World

Brief Overview of Salesforce’s Einstein Platform Services?—?APIs that allow to build AI-powered apps fast


GRU implementation in TensorFlow

MLPs (Multi-Layer Perceptrons) are great for many classification and regression tasks, but it is hard for MLPs to do classification and regression on sequences. In this code tutorial, a GRU is implemented in TensorFlow.


A Standard to build Knowledge Graphs: 12 Facts about SKOS

These days, many organisations have begun to develop their own knowledge graphs. One reason might be to build a solid basis for various machine learning and cognitive computing efforts. For many of those, it remains still unclear where to start. SKOS offers a simple way to start and opens many doors to extend a knowledge graph over time.


Why Cognitive Systems should combine Machine Learning with Semantic Technologies

Imagine you want to build an application that helps to identify wine and cheese pairings. Who will perform best? Applications solely based on machine learning, those ones which are based on experts’ knowledge only, or a combination of both?


Top Graphical Models Applications in Real World

Now we are going to explain the various Graphical Models Applications in real life such as – Manufacturing, finance, Steel Production, Handwriting Recognition etc. At last, we will discuss the case study about the use of Graphical Models in the Volkswagen.
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