Artificial intelligence or deep learning: Everybody talks about it and everybody uses it, including you! Of course you immediately have the evil terminator in mind wh
I use state-of-the-art NLP techniques to improve an existing pricing model in an online car market. Online car markets usually use technical car attributes for price prediction with sellers adding description texts to provide more details. In my thesis, I use these texts to improve the existing pricing model.
tl;dr: This blog post summarizes my masters‘ thesis. I use state-of-the-art NLP techniques to improve an existing pricing model in an online car market. Online
This article presents SeqPolicyNet, our Deep Learning approach to accessing information stored in an Elasticsearch instance given natural language questions.
tl;dr (spoiler alert): We’ve trained an advanced neural network to query Elasticsearch based on natural language questions. Our model, called SeqPolicyNet, incorporat
This article unveils the connections between artificial intelligence, machine learning and deep learning based on a simple example. It suits as an introduction for newbies as well as a reference point for advanced readers looking for more complex content.
There has always been a gap between the capabilities of men and machine. While computers were able to perform complex multiplications or store large amounts of data,
Machine learning as a service (MLaaS) bietet Unternehmen eine einfache Möglichkeit, Daten zu verarbeiten, Modelle zu trainieren und Prognosen zu erstellen. In diesem Artikel werden die Angebote von vier der größten Cloud-Anbieter vorgestellt: GCP, AWS, MS Azure und IBM Cloud/Watson.
Cloud Computing gewinnt durch sein flexibles Bereitstellungsmodell immer größere Bedeutung. Von Software (SaaS),Plattformen (PaaS) bis hin zur IT-Infrastruktur (IaaS)
In the last years, artificial neural networks (ANN) have successfully been applied across a number of tasks. However, designing well performing ANNs requires expert knowledge and experience. Neuroevolution aims at solving this difficult and often time-consuming process by using evolutionary techniques.
In the last years, artificial neural networks (ANN) have successfully been applied across a number of tasks, such as image classification, speech recognition and natu
In this article we will look at the history of Neuroevolution and present state-of-the-art work that was performed by Google, Uber and other companies.
Neuroevolution describes the evolution of Artificial Neural Networks for problems in the domain of supervised or reinforcement learning. This article is the result of
In iOS 11 Apple introduced Core ML, its own framework for Machine Learning on iPhone and iPad. In this article we show how to convert a trained TensorFlow Model and integrate it with an iOS app.
Machine learning and more precisely convolutional neural networks are an interesting approach for image classification on mobile devices. In the recent past it wasn
In this post we'll show how to integrate machine learning, more accurately a neural network, to recognize houseplants in an Android app—using TensorFlow Mobile directly on the device!
Nowadays, modern mobile devices are extremely powerful and enable new approaches. Even if it sounds like a platitude, it is clear that some of these approaches are ve
Recent improvements on the architecture and the training of Generative Adversarial Networks have rendered them applicable on a greater variety of problems, e.g sequential or discrete data. In this blog article we take a closer look on the general theoretical GAN architecture and its variations.
Neural networks are one of the technologies that have the potential to change our lives forever. Besides lots of applications and machines in the industry they have d
We built a text spotting (OCR) pipeline that out-performed Google Cloud Vision using semi-supervised Generative Adversarial Networks.
Despite all advances in machine learning due to the advent of deep learning, the latter has one major shortcoming: It requires a lot of data during the learning proce
In this blog series we explain how you can train and deploy a convolutional neural network for image classification to a mobile app using TensorFlow Mobile.
Smart Assistants, fancy image filters in Snapchat and apps like Prisma all have one thing in common—they are powered by Machine Learning. The use of Machine Learning
Neural networks are the basis of some pretty impressive recent advances in machine learning. From greatly improved translation to automatic transfer of painting style