Publications by Appsilon Data Science Blog
Shiny chat in few lines of code
Intro We live in a society heavily reliant upon communication, networking and information exchange. Think about all the chat apps that have recently popped out: WhatsApp, Messenger, Skype, Viber, Slack (not to mention Snapchat or Telegram). They have engrained themselves into our daily lives. You’d be hard pressed to find someone who doesn’t ...
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shiny.collections, Google Docs-like live collaboration in Shiny
A few weeks ago, our CTO Marek Rogala gave an engaging talk at the User Conference in Brussels. Despite being one of the last talks, he drew a crowd that filled the room and had significant viewership online. Marek’s talk was entitled shiny.collections: Google Docs-like live collaboration in Shiny. In short, he went over a package we built that...
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Zalando’s images classification using H2O with R
Fashion-MNIST About three weeks ago the Fashion-MNIST dataset of Zalando’s article images, which is a great replacement of classical MNIST dataset, was released. In the following article we will try to build a strong classifier using H2O and R. Each example is a 28×28 grayscale image, associated with a label from 10 classes: T-shirt/top Trous...
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How we built a Shiny App for 700 users?
One of our data scientists, Olga Mierzwa-Sulima spoke at the User Conference in Brussels to a packed house. The seats were full and there were audience members spilling out the doors. Source: https://twitter.com/matlabulous/status/882530484374392834 Olga’s talk was entitled ‘How we built a Shiny App for 700 users?’ She went over the main ...
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Zalando’s images classification using H2O with R
Fashion-MNIST About three weeks ago the Fashion-MNIST dataset of Zalando’s article images, which is a great replacement of classical MNIST dataset, was released. In the following article we will try to build a strong classifier using H2O and R. Each example is a 28×28 grayscale image, associated with a label from 10 classes: T-shirt/top Trous...
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How to internationalize your Shiny apps with shiny.i18n?
We pride ourselves on the fact that we work on some of the most difficult business applications of Shiny. These range from sales, manufacturing, management tools, to even satellite data analysis tools. Many of our clients include multinational enterprises that are continuously looking for new markets to enter. Most markets, however, have a common...
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Super excited for R promises
We at Appsilon are excited about RStudio introducing promises in R quite soon which is going to be a huge step forward in programming in R (we have already used futures and similar libraries to run code asynchronously, however this is going to be a standard and it looks like it’s going to be very easy to use). They support chaining which is a g...
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How to sample from multidimensional distributions using Gibbs sampling?
We will show how to perform multivariate random sampling using one of the Markov Chain Monte Carlo (MCMC) algorithms, called the Gibbs sampler. Random sampling with rabbit on the bed plane via GIPHY To start, what are MCMC algorithms and what are they based on? Suppose we are interested in generating a random variable with a distribution of ,...
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How to sample from multidimensional distributions using Gibbs sampling?
We will show how to perform multivariate random sampling using one of the Markov Chain Monte Carlo (MCMC) algorithms, called the Gibbs sampler. Random sampling with rabbit on the bed plane via GIPHY To start, what are MCMC algorithms and what are they based on? Suppose we are interested in generating a random variable with a distribution of ,...
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How we built a Shiny App for 700 users?
One of our senior data scientists, Olga Mierzwa-Sulima spoke at the userR! conference in Brussels to a packed house. The seats were full and there were audience members spilling out the doors. Source: https://twitter.com/matlabulous/status/882530484374392834 Olga’s talk was entitled ‘How we built a Shiny App for 700 users?’ She went over ...
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