Below you’ll find the complete code used to create the ggplot2 graphs in my talk The Good, the Bad and the Ugly: how (not) to visualize data at this year’s data2day conference. You can find the German slides here: You can also find a German blog article accompanying my talk on codecentric’s blog. If you have questions or would like to talk about this article (or something else data-related), you can now book 15-minute timeslots with me (it’s free - one slot available per weekday):
Workshop material Because this year’s UseR 2020 couldn’t happen as an in-person event, I have been giving my workshop on Deep Learning with Keras and TensorFlow as an online event on Thursday, 8th of October. You can now find the full recording of the 2-hour session on YouTube and the notebooks with code on Gitlab. If you have questions or would like to talk about this article (or something else data-related), you can now book 15-minute timeslots with me (it’s free - one slot available per weekday):
I have been working with Keras for a while now, and I’ve also been writing quite a few blogposts about it; the most recent one being an update to image classification using TF 2.0. However, in my blogposts I have always been using Keras sequential models and never shown how to use the Functional API. The reason is that the Functional API is usually applied when building more complex models, like multi-input or multi-output models.
Recently, I have been getting a few comments on my old article on image classification with Keras, saying that they are getting errors with the code. And I have also gotten a few questions about how to use a Keras model to predict on new images (of different size). Instead of replying to them all individually, I decided to write this updated version using recent Keras and TensorFlow versions (all package versions and system information can be found at the bottom of this article, as usual).
Alright, this is it: I am officially back! :-D I have not written any blogposts for over a year. Last year, I had the cutest baby boy and ever since then, I did not get around to doing much coding. One of the reasons was that, unfortunately, we did not have the easiest of starts with the little one. Feeding problems led to weight gain problems, so we had to weigh him regularly.
In our next MünsteR R-user group meetup on Tuesday, July 9th, 2019, we will have two exciting talks about Word2Vec Text Mining & Parallelization in R! You can RSVP here: https://www.meetup.com/de-DE/Munster-R-Users-Group/events/262236134/ Thorben Hellweg will talk about Parallelization in R. More information tba! Maren Reuter from viadee AG will give an introduction into the functionality and use of the Word2Vec algorithm in R. Text data in its raw form cannot be used as input for machine learning algorithms.
Today, I am finally getting around to writing this very sad blog post: Before you take my DataCamp course please consider the following information about the sexual harassment scandal surrounding DataCamp! UPDATE from April 26th: Yesterday, DataCamp’s CEO Jonathan Cornelissen issued an apology statement and the DataCamp Board of Directors wrote an update about the situation and next steps (albeit somewhat vague) they are planning to take in order to address the situation.