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.

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This spring, I’ll be giving talks at a couple of Meetups and conferences: March, 26th: At the data lounge Bremen, I’ll be talking about Explainable Machine Learning April, 11th: At the Data Science Meetup Bielefeld, I’ll be talking about Building Interpretable Neural Networks with Keras and LIME May, 14th: At the M3 conference in Mannheim, a colleague and I will give our workshop on building production-ready machine learning models with Keras, Luigi, DVC and TensorFlow Serving

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In our next MünsteR R-user group meetup on Tuesday, April 9th, 2019, we will have two exciting talks: Getting started with RMarkdown and Trying to make it in the world of Kaggle! You can RSVP here: http://meetu.ps/e/Gg5th/w54bW/f Getting started with RMarkdown First, Niklas Wulms from the University Hospital, Münster will give an introduction to RMarkdown: He started using R in 2018 and learnt the advantages of using only one framework of free software and code.

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Disclaimer: Manning publications gave me the ebook version of Beyond Spreadsheets with R - A beginner’s guide to R and RStudio by Dr. Jonathan Carroll free of charge. Beyond Spreadsheets with R shows you how to take raw data and transform it for use in computations, tables, graphs, and more. You’ll build on simple programming techniques like loops and conditionals to create your own custom functions. You’ll come away with a toolkit of strategies for analyzing and visualizing data of all sorts using R and RStudio.

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In the past, I have written and taught quite a bit about image classification with Keras (e.g. here). Text classification isn’t too different in terms of using the Keras principles to train a sequential or function model. You can even use Convolutional Neural Nets (CNNs) for text classification. What is very different, however, is how to prepare raw text data for modeling. When you look at the IMDB example from the Deep Learning with R Book, you get a great explanation of how to train the model.

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UPDATE: Before you take this course please consider the info about the sexual harrassment scandal surrounding DataCamp! I am very happy to announce that (after many months) my interactive course on Hyperparameter Tuning in R has now been officially launched on Data Camp! Course Description For many machine learning problems, simply running a model out-of-the-box and getting a prediction is not enough; you want the best model with the most accurate prediction.

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These are slides from a lecture I gave at the School of Applied Sciences in Münster. In this lecture, I talked about Real-World Data Science and showed examples on Fraud Detection, Customer Churn & Predictive Maintenance. Real-World Data Science (Fraud Detection, Customer Churn & Predictive Maintenance) von Shirin Glander The slides were created with xaringan.

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Dr. Shirin Elsinghorst

Biologist turned Bioinformatician turned Data Scientist

Data Scientist

Münster, Germany