Digital-Thinking
A blog about machine learning and software development
Besides computer vision, artificial neural networks (ANNs) are also very popular in natural language processing. Automatic translation or sentiment analysis of reviews are well known areas, where (recurrent) neural networks are used a lot. Around natural language understanding, there are…
Just about one year ago, I was trying to make the distinction between data science and data engineering. But in the past year a new job role has become very popular (at least I noticed it in job postings and…
In this post I will show how to combine features from natural language processing with traditional features (meta data) in one single model in keras (end-to-end learning). This can be done, by using multiple inputs models. Problem definition In applied…
When looking on Quora, reddit etc. people often ask how much math is required in machine learning. In addition some courses on udemy or other online learning platforms require a lot of prerequisites. In this post I try to make…
In this post I want to show you a very nice technology stack, which can be used to manage your passwords in Keepass, connect it to your web browser and make it possible to open ssh and scp connections easily….
In this post I will show, how to report jmx metrics to logstash via TCP on a push based way, without changing java code from an existing application.
Data engineering is the link between data science and software engineering. Data engineers often work together with data scientists and analysts and help them to do their job efficiently. Moreover they are responsible for transforming models and prototypes built by…
In the last months I was working on a deep learning project. The goal was to dig into Tensorflow and deep learning in gerneral. For this purpose I re-implemented a paper from January 2016 called convolutional pose machines , which uses deep…
This post is about data structures and how they compare in performance, when considering the CPU Prefetch mechanism and other cache effects. It shows that LinkedLists are bad in the most cases and how to deal with variable sharing.
When i started to make use of Scala with Apache Spark, the first thing I thought about the language was “WTF is this?”. I just want to give you an very simple example:
| 1 2 3 4 | val map = list.map(item => (item.getId(), item)) .filter(_._1 % 2 == 0) .sortBy(_._1).reverse .toMap |
For a C/C++/Java programmer this piece…