Mar

15,

2021

On pythonic tracks

<div style="text-align: justify;">Python has established itself as a quasi-standard in the field of machine learning over the last few years, in part due to the broad availability of libraries. It is logical that Oracle did not really like to watch this trend — after all, Java has to be widely...

Blog, Generative AI & Agents

Understanding Language is a Frontier for AI

Feb

16,

2021

Understanding Language is a Frontier for AI

<div style="text-align: justify;">In recent years we have seen a lot of breakthroughs in AI. We now have deep learning algorithms beating the best of the best in games like chess and go. In computer vision these algorithms now recognise faces with the same accuracy as humans. Except they don’t, they...

Blog, ML & Deep Learning

Real-time anomaly detection with Kafka and Isolation Forests

Jan

2021

Real-time anomaly detection with Kafka and Isolation Forests

<div style="text-align: justify;">Anomalies - or outliers - are ubiquitous in data. Be it due to measurement errors of sensors, unexpected events in the environment or faulty behaviour of a machine. In many cases, it makes sense to detect such anomalies in real time in order to be able to react...

AI Developer Tools, Blog

Let’s visualize the coronavirus pandemic

Dec

16,

2020

Let’s visualize the coronavirus pandemic

<div style="text-align: justify;">Since February, we have been inundated in the media with diagrams and graphics on the spread of the coronavirus. The data comes from freely accessible sources and can be used by everyone. But how do you turn the source data into a data set that can be used...

Blog, ML Basics & Principles

Explainability – a promising next step in scientific machine learning

May

2020

Explainability – a promising next step in scientific machine learning

With the emergence of deep neural networks, the question has arisen how machine learning models can be not only accurate but also explainable. In this article, you will learn more about explainability and what elements it consists of, and why we need expert knowledge to interpret machine learning results to...

Blog, MLOps, LLMOps & Pipelines

Continuous Delivery for Machine Learning

Apr

14,

2020

Continuous Delivery for Machine Learning

In modern software development, we’ve grown to expect that new software features and enhancements will simply appear incrementally, on any given day. This applies to consumer applications such as mobile, web, and desktop apps, as well as modern enterprise software. We’re no longer tolerant of big, disruptive software deployments. ThoughtWorks...

Blog, ML Basics & Principles

Tutorial: Explainable Machine Learning with Python and SHAP

Feb

11,

2020

Tutorial: Explainable Machine Learning with Python and SHAP

Machine learning algorithms can cause the “black box” problem, which means we don’t always know exactly what they are predicting. This may lead to unwanted consequences. In the following tutorial, Natalie Beyer will show you how to use the SHAP (SHapley Additive exPlanations) package in Python to get closer to...

AI Developer Tools, Blog

Jan

28,

2020

Deep Learning: Not only in Python

Although there are powerful and comprehensive machine learning solutions for the JVM with frameworks such as DL4J, it may be necessary to use TensorFlow in practice. This can, for example, be the case if a certain algorithm exists only in a TensorFlow implementation and the effort to port the algorithm...

Tag

On pythonic tracks

Understanding Language is a Frontier for AI

Real-time anomaly detection with Kafka and Isolation Forests

Let’s visualize the coronavirus pandemic

Explainability – a promising next step in scientific machine learning

Continuous Delivery for Machine Learning

Tutorial: Explainable Machine Learning with Python and SHAP

Deep Learning: Not only in Python

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