Introduction Some time ago I wrote about the support for R users within Dataiku. The software can really boost the productivity of R users by having: Managed R code environments, Support for publishing of R markdown files and shiny apps … Continue reading →

Create a predictive model with the h2o package. H2o is a fantastic open source machine learning platform with many different algorithms. There is Graphical user interface, a Python interface and an R interface. Suppose you want to create a predictive … Continue reading →

At the beginning of the new year I always want to clean up my photos on my phone. It just never happens. So now (like so many others I think) I have a lot of photos on my phone from … Continue reading →

Introduction Playing around with PyTorch and R Shiny resulted in a simple Shiny app where the user can upload a flower image, the system will then predict the flower species. Steps that I took Download labeled flower data from the … Continue reading →

A couple of weeks ago, the first of September we had satRday in Amsterdam (The Netherlands) a fantastic event hosted by GoDataDriven. Now the great talks, including my 10 minute lightning talk on text2vec are online. My talk The satRday … Continue reading →

Introduction It is 35 degree Celsius out side, we are in the middle of the ‘slow news season’, in many countries also called cucumber time.  A period typified by the appearance of less informative and frivolous news in the media. … Continue reading →

The municipal services of Amsterdam (The Netherlands) is providing open panorama images. See here and here. A camera car has driven around in the city, and now you can download these images. Per neighborhood of Amsterdam  I randomly sampled 20 … Continue reading →

Introduction My son is 8 years old and he has shown a lot of interest in cars, which is strange because I have zero interest in cars. But he is driving me crazy when we have a car ride: “dad … Continue reading →

Introduction Not long ago I was reading on t-Distributed Stochastic Neighbor Embedding (t-sne), a very interesting dimension reduction technique, and on Mel frequency cepstrum a sound processing technique. Details of both techniques can be found here and here. Can we combine … Continue reading →

Introduction On the 8th, 9th and 10th of December I participated at the IKEA hackaton. In one word it was just FANTASTIC! Well organized, good food, and participants from literally all over the world, even the heavy snow fall on … Continue reading →

Introduction Market Basket Analysis or association rules mining can be a very useful technique to gain insights in transactional data sets, and it can be useful for product recommendation. The classical example is data in a supermarket. For each customer … Continue reading →

Introduction Recently, Dataiku 4.1.0 was released, it now offers much more support for R users. But wait a minute, Data-what? I guess some of you do not know Dataiku, so what is Dataiku in the first place? It is a … Continue reading →

Introduction I often see advertisement for The Bold and The Beautiful, I have never watched a single episode of the series. Still, even as a data scientist you might be wondering how these beautiful ladies and gentlemen from the show … Continue reading →

Introduction Two things that recently came to my attention were AutoML (Automatic Machine Learning) by h2o.ai and the fashion MNIST by Zalando Research. So as a test, I ran AutoML on the fashion mnist data set. H2o AutoML As you all … Continue reading →

Introduction My first car was a 13 year Mitsubishi Colt, I paid 3000 Dutch Guilders for it. I can still remember a friend that would not like me to park this car in front of his house because of possible … Continue reading →

Introduction If I mention Power BI to fellow data scientists I often get strange looks. However, I quite like the tool, it is an easy and fast way to share results, KPI’s and graphs with others. With the latest release, Power BI now … Continue reading →

Introduction Not so long ago there was a nice dataiku meetup with Pierre Gutierrez talking about transfer learning. RStudio recently released the keras package, an R interface to work with keras for deep learning and transfer learning. Both events inspired … Continue reading →

Introduction Not so long ago RStudio released the R package ‘reticulate‘, it is an R interface to Python. Of course, it was already possible to execute python scripts from within R, but this integration takes it one step further. Imported … Continue reading →

Introduction Because it is Friday, another ‘playful and frivolous‘ data exercise ? IKEA is more than a store, it is a very nice experience to go through. I can drop of my two kids at smàland, have some ‘quality time’ … Continue reading →

Intro In an earlier post I talked about Spark and sparklyR and did some experiments. At my work here at RTL Nederland we have a Spark cluster on Amazon EMR to do some serious heavy lifting on click and video-on-demand … Continue reading →