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.
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.
Forecasts for intermittent data are often difficult. Torben examines whether the Statsforecast package can be used and describes which evaluation methods are useful.
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.
Successful AI implementation depends to a large extent on the corporate culture.
This article sheds light on how fundamental values, norms and behaviors in the company support the introduction of AI.
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.
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!
In this blog post, Michael describes why data storytelling goes far beyond pure data quality and how it enables companies to realize the full potential of their data.
Sara vividly describes her journey to becoming a certified project manager.
In addition to her personal insights, you will find helpful tips on PMP certification.
We review Tensorflow’s concept of ragged tensors, which were introduced at the end of 2018. We explain their basic structure and why they are useful.
The term “preventive maintenance” is often used in connection with the optimization of maintenance plans.
What is information entropy? Let’s assume that in summer we want to send our friends a telegram from Hamburg to St. Petersburg every day about the weather conditions: sunny, slightly cloudy, overcast, rainy.
This post presents a modern approach to estimate an individual probability curve for the acceptance of an offer from historical accepted and rejected transaction data.
Traditionally, offer prices for products or services are charged on the basis of the costs incurred, plus a target margin. Since the end of the last century, there has been a second approach to setting bid prices…
Publications are the basis of scientific work: scientists and practitioners all over the world use these results.
Frequent problems that we are confronted with can be traced back to a (multidimensional) regression or a classification. Starting from a set of characteristics, regression attempts to represent the dependency between the characteristics and a target variable as a function.
Based on Bayes’ theorem, Bayesian statistics has developed, which is used in the context of inductive statistics and machine learning to estimate parameters and test hypotheses.
Here it is: the m2hycon blog! After 25 years in mathematical consulting for companies, we have now decided to use this medium as well.
Do you have questions about our blog posts? Contact our editorial team…
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