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.
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
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.
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.
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.