Is your company ready for the Internet of Things?
Wish to master the challenges of the Internet of Things? Then you need to know your IoT maturity level. Discover yours with our IoT Readiness Assessment
6 steps for successful IoT projects
Would you like to implement digital transformation in the Internet of Things? No problem with our IoT adoption framework!
Child´s game "Guess Who": for Data Science enthusiasts
Read part 2 of the article to find out how Data Science can be used to develop the perfect winning strategy for the children's game "Guess Who?".
Data Science for kids: how to win at "Guess Who?"
The child's game "Guess who?": How to win and which question you should definitely ask first in the game is shown in part 1 of the article series.
Recommender systems 3: Personalized recommender systems
Teil 3 zeigt die Möglichkeiten personalisierter Recommender Systeme, die Vorteile von Machine-Learning-Methoden & die Erfolgsmessung von Empfehlungssystemen.
Recommender systems 2: Non-personalized processes
This blog post provides an overview of the underlying algorithms of modern recommender systems and facilitates the selection of suitable recommenders.
Great Expectations
Data quality checks are important, but not always possible due to a lack of tools. This article shows how to close this gap using Pipeline Test.
The second day of PAW 2019
On day two of PAW 2019 in Berlin we see how data science use cases can be integrated into companies in a value-generating way.
The first day of PAW 2019
So that was Day 1 at Predictive Analytics World. Our colleague Dr. Michael Allgöwer reports on his impressions and explains the benefits of entropy.
Building Blocks for intelligent Applications
Our blog post gives an overview of AWS AI Services: One way to integrate Artificial Intelligence into intelligent applications.
Neural averaging ensembles
Find out how ideas from ensemble learning can be used to tailor neural network architectures for applications based on tabular data.
Reinforcement Learning & Bayesian Statistics - Part 2
TensorFlow Probability is a hot new tool from Google. We blend it with some Bayesian Statistics to make reinforcement learning less data-hungry.
Reinforcement Learning & Bayesian Statistics - Part 1
In this article, you will learn how Bayesian Statistics is related to reinforcement learning and might make the latter less data-hungry.
Are you data-driven? Or is it the noise that drives you?
A modern organization should base decisions on data, not gut feeling. But what if that data contains more random fluctuation than meaningful information?
Causal inference - the eternal question of "why"
Can we identify causes and effects in our data? Find the answer in our latest blog post - read it now!
Serverless Data Science on AWS
Read the blog post now and learn about the possibilities of a "serverless" approach in general and with an example - read it now!
Best Practice: Working with Paths in Python - Part 2
Read the second part of our blog post to see how you can save time cataloging data. Read it now!
Best Practice: Working with Paths in Python - Part 1
How you can save time cataloging folders or drives can be read in our first part of the blog post! Read it now!
How Data Science can help choosing the right romper suit
Never buy the wrong clothing size for your children - Data Scientist & dad Dr. Michael Allgöwer knows how easy it is with Data Science!
The Basic Ideas behind Recommendation Systems
How your company can benefit from the implementation of Recommendation Systems, read here!
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