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!
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…
Vielen Dank für Ihr Interesse an den Leistungen von m²hycon. Wir freuen uns sehr, von Ihrem Projekt zu erfahren und legen großen Wert darauf, Sie ausführlich zu beraten.
Thank you for your interest in m²hycon’s services. We look forward to hearing about your project and attach great importance to providing you with detailed advice.
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