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.
In this blog post, Jannik will show you how to deploy your machine learning models as a REST API and how to make requests to the API from within your Python code.
Are you confused by Bayesian statistics? If you understand Ridge regression, one of the most common Bayesian models is within your reach! This post gives a brief intro to Bayesian thinking and shows you just how similar Ridge regression is to Bayesian linear regression by walking you through the math and exploring how coefficient estimates from both models compare.
A new field of Machine Learning is born: Causal Machine Learning. Learn here what it is and why it is crucial for the future of Data Science.