Effortless Time Series Feature Generation: A Practical Approach for Simple Models
Good features for a time series analysis can also be created automatically. We test it out with the Python package Functime.
The blog about and around data science
Category: Data Science
Data Science
ChatGPT-o1 vs. ChatGPT-4o – Part 2
More comparisons between ChatGPT-o1 and ChatGPT4o, what’s new and when is which AI more suitable?
Data Science
ChatGPT-o1 vs. ChatGPT-4o
ChatGPT-o1 compared to its predecessor ChatGPT4o, what new features are there and when is which AI more suitable? Our data scientist Mark put the algorithms to the test.
Data Science
Geostatistics against malaria: recognizing and combating insecticide resistance
Malaria remains one of the biggest health challenges in tropical regions. In this article you will learn how modern geostatistics against malaria is used to map resistance, identify trends and develop effective strategies to combat this disease.
Data Science
News
AI as a competitive advantage: 8 groundbreaking factors for companies
With the rapid development in the field of AI, it is important to keep an overview. We address 8 factors that are important for the success of AI in companies.
Data Science
Expert knowledge
News
Practice
Leveraging Advanced Forecasting Techniques with StatsForecast: A Case Study
Forecasts for intermittent data are often difficult. Torben examines whether the Statsforecast package can be used and describes which evaluation methods are useful.
Data Science
Expert knowledge
News
Practice
The importance of unit tests and testing in general in data science
Testing in data science projects is often neglected. In this blog post, you can find out what the consequences are and how it can be done better.
Data Science
News
Technology trends
Python package management: A new, promising tool called UV
The new Python package management tool UV offers some interesting advantages over previous tools. Find out what they are and what we expect from UV in this blog post.
Data Science
News
Project Management
Four Pitfalls of Agile Work in Data Science Teams (And How You Can Avoid Them)
Agile project management can be challenging in data science teams.
Natalia describes the stumbling blocks that can occur and how to overcome them in this blog post!
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Dr. Michael Mederer
