Title 5 Types of Machine Learning Algorithms

5 Types of Machine Learning Algorithms (With Use Cases)

Fran Peric Blog, Data Science

We are encountering Machine Learning algorithms in our daily lives. Some are practical, like Google Translate; others are fun, like Snapchat Filters. Our interaction with artificial intelligence will most likely increase in the next few years. Given the potential impact of Machine Learning models on our future lives, Fran Peric presents to you the five branches of Machine Learning and their key concepts.

How Scrum Can Be Used for to Data Science Projects

Whitepaper on Data Strategy.Whitepaper: How Scrum Can Be Used for Data Science Projects.In this whitepaper, 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. In recent …

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.

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

DATA SCIENCE WHITEPAPER ON AI STRATEGY.Whitepaper: 35 AI and Machine Learning Use Cases for the Retail & Consumer Goods Industry.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. Artificial intelligence …

How to Build Trust With Explainable AI

Data Science Whitepaper on Data Strategy.Whitepaper: How to Build Trust With Explainable AI.This whitepaper provides an overview of possible applications, advantages, methods, and challenges in employing Explainable AI in companies. Artificial intelligence (AI) in companies is no longer a new trend. Nevertheless, the potential for AI is far from exhausted and still offers enormous opportunities. for people and AI to …

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

Data Science Whitepaper on Machine Learning.Whitepaper: Machine Learning in the Cloud – Comparing AWS, Azure, and GCPIn this white paper we provide you with an overview of the offerings of the three largest providers for cloud computing, AWS, Azure and GCP. We also look at how these providers lower the barriers to successful ML projects. Digital transformation is a challenge …

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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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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.

AI Training in Companies

Data Science Whitepaper on AI Training.Whitepaper: AI Training in CompaniesIn 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. The further education of employees in …

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.