Whitepaper: How Scrum Can Be Used for Data Science Projects

Jakob Gepp Blog, Data Science

In the whitepaper “How Scrum Can Be Used for Data Science Projects”, you will get an overview of the project management technique Scrum with regard to the typical process of a data science project. Based on this, we present the biggest challenges and propose solutions for the integration of Scrum in your data science projects.Read the Management Summary of this whitepaper here.

Whitepaper: 35 AI and Machine Learning Use Cases for the Retail and Consumer Goods Industry

Jan Fischer Blog

This whitepaper aims to present an overview of possible AI use cases in this specific industry. It provides a clear, comprehensive collection of 35 use cases to inspire the reader to think about potential applications in their own business. We focus on what you can do and why your company would benefit from the integration of AI and machine learning capabilities.

Whitepaper: How To Build Trust With Explainable AI

Verena Eikmeier Blog, Data Science

Today, a multitude of methods make it possible to explain even complex AI systems. Even though there are several challenges to be considered, the benefits of XAI in companies are immense. This whitepaper provides an overview of possible applications, advantages, methods, and challenges in employing XAI in companies and thus serves as a guide to this essential future topic.

5 Practical Examples of NLP Use Cases

Felix Plagge Blog, Data Science

Due to recent achievements in deep learning, several different NLP (“Natural Language Processing”) tasks can now be solved with outstanding quality.
In this article, you will learn how NLP applications solve various business problems through five practical examples, which ensured an increase in efficiency and innovation in their field of application.

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Whitepaper: Machine Learning in the Cloud – Comparing AWS, Azure, and GCP

Alexander Blaufuss Blog, Data Science

In order for companies to continue to be successful in a digital, software and data-driven age, the necessary technical prerequisites must be established. The use of cloud technology is seen as an important element in this process.
In this whitepaper we provide an overview of the range of services offered by the three largest providers for cloud computing, AWS, Azure and GCP.

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The 5 Most Important Use Cases for Computer Vision

Oliver Guggenbühl Blog, Data Science

The foundations for image recognition and computer vision were already laid down in the 1970s. However, it is only in recent years that the field has found increasing application outside research. This article presents five selected and particularly promising use cases from different industries, which are either already in production or promise significant changes in their respective fields in the coming years.

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Whitepaper: AI Training for Executives

Fabian Müller Blog, Data Science

Im Whitepaper “Künstliche Intelligenz Weiterbildung für Führungskräfte” zeigen wir Ihnen anhand der Case Study „AI Basics for Executives“ beispielhaft, wie eine erfolgreiche Umsetzung eines ausdifferenzierten Weiterbildungskonzepts aussehen kann. Hierbei wurde, speziell für Führungskräfte eines international agierenden Konzerns, ein Weiterbildungsformat entwickelt, das die Zielgruppe des mittleren bis gehobenen Managements auf die anstehende KI-Transformation vorbereitet.

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New Trends in Natural Language Processing – How NLP Becomes Suitable for the Mass-Market

Dominique Lade Blog, Data Science

NLP (Natural Language Processing) generally describes the computer-aided processing of human language. This includes both written and spoken language. In this article, we show different NLP case studies and explain how, within only a few years, the barriers to market entry have been lowered to such an extent that today every company can use NLP to solve their individual business problems.

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Whitepaper: AI Training in Companies

Alexander Niltop Blog, Data Science

The further education of employees in artificial intelligence (AI) is one of the central tasks for establishing AI in one’s own company. In this white paper we explain the tasks & responsibilities of the individual roles of a Data Science and AI team. Building on this, we will show why internal training and support of external service providers are the key to building a successful AI strategy.

5 Technologies That Every Data Engineer Should Know

Andre Münch Blog, Data Science

This article presents five technologies that every data engineer should know and master for his daily work. Spark as a data processing tool in the big data environment, Kafka as a streaming platform, Airflow, and serverless architecture for coordination and orchestration are presented. Before that, the importance and role of SQL (Structured Query Language) and relational databases will be discussed.