Feb

19,

2024

OpenAI Embeddings

Embedding vectors (or embeddings) play a central role in the challenges of processing and interpretation of unstructured data such as text, images, or audio files. Embeddings take unstructured data and convert it to structured, no matter how complex, so they can be easily processed by software. OpenAI offers such embeddings,...

Blog, ML Basics & Principles

Feb

2024

Address Matching with NLP in Python

Discover the power of address matching in real estate data management with this comprehensive guide. Learn how to leverage natural language processing (NLP) techniques using Python, including open-source libraries like SpaCy and fuzzywuzzy, to parse, clean, and match addresses. From breaking down data silos to geocoding and point-in-polygon searches, this...

Blog, ML Basics & Principles

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, 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

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

OpenAI Embeddings

Address Matching with NLP in Python

On pythonic tracks

Real-time anomaly detection with Kafka and Isolation Forests

Let’s visualize the coronavirus pandemic

Tutorial: Explainable Machine Learning with Python and SHAP

Deep Learning: Not only in Python

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