In this article, Jonas Braun reports on the most common way to use Kubernetes: with cloud providers like Google GCP, Amazon AWS or Microsoft Azure. In the article, he looks at how to deploy these containers (i.e. applications or models) reliably and scalably for customers, other applications, internal services or computations with Kubernetes. Finally, the article gives an outlook on tools and further developments.
Deploying and monitoring machine learning projects is a complex undertaking. In this article, John Vicente presents the typical challenges along the machine learning workflow and describes a possible solution platform with MLflow. In addition, we present three different scenarios that can be used to professionalize machine learning workflows.
Did you want to know how to build a web frontend in Python? In the 4th and last part of our blog series, we develop an interactive game. The user has to guess the car brand and model. Do you think you can beat our AI?
In the third part of our blog series, we cover an essential topic that has gained significant traction in the ML-community in the past years: Explainability. Explainable AI is essential to establish trust in the models we develop. We discuss various approaches for CNN networks, with a particular focus on the Grad-CAM method.
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.
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.
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.
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.
In this article, our colleague Stephan is first going to explain how GANs work in general. Afterward, he will discuss several use cases that can be implemented with the help of GANs, and to sum up, he will present current trends that are emerging in the area of generative networks.
More and more companies recognize the potential of artificial intelligence and develop their own ML models. At the same time, these companies are often faced with the challenge of making these models available to users internally and thereby generating added value from the model. In this article, we show what such challenges can be and how Docker enables companies to meet them.