Virtually everyone has had an online experience where a website makes personalized recommendations in hopes of future sales or ongoing traffic. Amazon tells you “Customers Who Bought This Item Also Bought”, Udemy tells you “Students Who Viewed This Course Also Viewed”. And Netflix awarded a $1 million prize to a developer team in 2009, for an algorithm that increased the accuracy of the company’s recommendation system by 10 percent. Without further ado, if you want to learn how to build a recommender system from scratch, let’s get started.
A Bayesian introduction to statistical classification problems
For many years, I actively avoided the data.table package and preferred to utilize the tools available in either base R or dplyr for data aggregation and exploration. However, over the past year, I have come to realize that this was a mistake. Data tables are incredible and provide R users with a syntatically concise and efficient data structure for working with small, medium, or large datasets. While the package is well documented, I wanted to put together a series of posts that could be useful for those who want to get introduced to the data.table package in a more task oriented format.
An interactive infographic can be used to communicate a lot of information in an engaging way. With the right tools, they are also relatively straightforward to create. In this post, I show step-by-step how to create this interactive infographic, using Canva, Displayr and R code. The interactive example is designed so that the user can change the country and have the infographic update automatically. Tools used to create an interactive infographic: Canva is used to create the base infographic. The calculations, charting, and automatic text-writing are performed using the R language. It is all hooked up with Displayr.
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 great way of building clean code by piping computations that take a long time.
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