Blog Archives

BIKE SERVICES API + SHINY = NICE APP

Hi everyone, In this blog post, I will be short and I will introduce our shiny application on bike self-service stations. Your browser does not support the video tag. The code is in 2 parts, the ui.R file for the interface and the server.R file for the backend. You can check the code on GitHub if you want to download...

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Teaching Luxembourgish to my computer

Teaching Luxembourgish to my computer

How we taught a computer to understand Luxembourguish Today we reveal a project that Kevin and myself have been working on for the past 2 months, Liss. Liss is a sentiment analysis artificial intelligence; you can let Liss read single words or who...

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Analysis of the Renert – Part 3: Visualizations

Analysis of the Renert – Part 3: Visualizations

This is part 3 of a 3 part blog post. This post uses the data that was scraped in part 1 and prepared in part 2. Now that we have the data in a nice format, let’s make a frequency plot! First let’s load the data and the packages: library("tidyverse") library("ggthemes") # To use different themes and colors renert_tokenized = readRDS("renert_tokenized.rds") Using the ggplot2...

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Analysis of the Renert – Part 2: Data Processing

Analysis of the Renert – Part 2: Data Processing

This is part 2 of a 3 part blog post. This post uses the data that we scraped in part 1 and prepares it for further analysis, which is quite technical. If you’re only interested in the results of the analysis, skip to part 3! First, let’s load the data that we prepared in part 1. Let’s start with the...

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Analysis of the Renert – Part 1: Scraping

Analysis of the Renert – Part 1: Scraping

This is part 1 of a 3 part blog post. This post presents the Luxembourgish language as well as the literary work I am going to analyze using the R programming language. Part 2 deals with preparing the data for analysis, and finally part 3 is the analysis. Hope you enjoy! Luxembourg and the Luxembourgish language Luxembourg is a small European...

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Churn Analysis – Part 2: Indicators

Churn Analysis – Part 2: Indicators

Hello everyone, In the last post we have decided to continue our study with the logistic regression. We have obtained the following ROC curve with an area under the curve (AUC) of 0.843. Now we imagine 2 scenarios. In the first one, we suppose we have a large budget and we want to target many customers. In the second one, we...

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Churn Analysis: Indicators (Part 2)

Churn Analysis: Indicators (Part 2)

Hello everyone, In the last post we have decided to continue our study with the logistic regression. We have obtained the following ROC curve with an area under the curve (AUC) of 0.843. Now we imagine 2 scenarios. In the first one, we suppose we have a large budget and we want to target many customers. In the second one, we...

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Churn Analysis – Part 1: Model Selection

Churn Analysis – Part 1: Model Selection

Hello everyone, Today we will make a churn analysis with a dataset provided by IBM. You can find the dataset here. What is a churn? We can shortly define customer churn (most commonly called “churn”) as customers that stop doing business with a company or a service. There are customer churns in different business area. In this post, we will focus on the...

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Churn Analysis: Model Selection (Part 1)

Churn Analysis: Model Selection (Part 1)

Hello everyone, Today we will make a churn analysis with a dataset provided by IBM. You can find the dataset here. What is a churn? We can shortly define customer churn (most commonly called “churn”) as customers that stop doing business with a company or a service. There are customer churns in different business area. In this post, we will focus on the...

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Map unemployment using R with ggplot2

Map unemployment using R with ggplot2

In this blog post, I show various ways to create maps using R. You’ll need to install a lot of packages and download two data sets; the unemployment rate in Luxembourg as well as a shapefile. To get the unemployment rate in Luxembourg, you can take a look at our previous blog post or simply run the following lines: library(rvest) library(dplyr) library(purrr) library(janitor) library(tidyr) page_unemp =...

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