Deploying (Small) Applications It Is Too Complicated in Many Cases — So let’s face it. A lot of code is written by people who aren’t software engineers. The companies they work in are not software first. They are experts in a certain domain with coding skills. Maybe they are a really good coder, but most likely they try to solve a…

Why does it have to be so freaking complicated? — Jupyter notebook and the IDE-like Jupyter Lab are really popular among data scientists and researchers in general. It’s a great tool to explore datasets by code, do simple computations, plot data and results, and much more. I like to use Jupyter notebooks for many reasons when trying new things or…

Without Data, You Will Be Lost — The Data-Economy Is Here During the last 10 to 15 years, the economy has undergone a massive shift towards a data-centric economy. It all started in the tech sector, where data is used to provide valuable services. Most people driving cars are using either Apple or Google maps for real-time traffic information nowadays. …

But Nobody Is Willing to Make an Effort to Actually Use It. — Story Time My time as a researcher and software developer in the field of radar simulations has been somewhat frustrating due to several reasons: Most of the time is spent coding something that nobody besides me will ever use. If the results are any good, suddenly people want me to simulate something…

Most scientists are unprepared for the ongoing shift towards computational sciences for data exploration. — The real heroes of science are not the scientist but all the other people that make it work in the background: lab assistants/managers craftspeople measurement engineers IT personnel … Without these supporting roles most (applied) sciences wouldn’t produce many results. In the past technical departments created supporting positions for lab…

Synthetic Data — The Road to Data-Centric AI — A lot of AI projects do not have enough good data to train meaningful models. The more complicated the application is the harder it becomes to get your hands on good data. …

Artificial Data for AI in Healthcare — The demand for intelligent data-driven systems is increasing in all areas of our lives. Application areas are found in medical imaging, autonomous driving, smart homes and many more. For such systems to work robustly and reliably, they need large amounts of training data. This training data needs to be labeled…