Build something great with our Open Source Products

We belive in the open source concept and are an active part of the open source community. Apart from joing conferences such as the JupyterCon and the EuroSciPy, we actively develop our own open source projects.


ipyannotator - the infinitely hackable annotation framework. Even though much less glamorous than developing new machine learning models, the annotation process and the required tooling is often one of the most critical aspects of real world Machine Learning projects.

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This repository allows you to use Factorization Machines in Python (2.7 & 3.x) with the well known scikit-learn API. All performance critical code has been written in C and wrapped with Cython. fastFM provides stochastic gradient descent (SGD) and coordinate descent (CD) optimization routines as well as Markov Chain Monte Carlo (MCMC) for Bayesian inference.

Checkout on GitHub

As winner of the Discovery Challenge ChAT - Palaimon presents at the ECML 2020

Leaderboard at the University of Würzburg "Team voyTECH"

Palaimon presents ipyannotator at theJupyterCon 2020

ipyannotator - the infinitely hackable annotation framework