… of machine learning and clarify its difference from statistical inference. Then, we review
Scikit-learn, a machine learning package … The Scikit-learn package includes implementations of a …

… This paper aims to evaluate the performance of a set of machine learning packages when
running trained models on different edge hardware platforms. By comparing the latency, …

… We have presented the software package Chemprop, a powerful toolbox for machine
learning of the chemical properties of molecules and reactions. Significant improvements have …

… mlr3proba leverages these packages by connecting a multitude of machine-learning … by
machine learning and support for high-dimensional data. Interfacing other packages in the mlr3 …

… 5.3 Auto machine learning … We use auto machine learning as the basis for the before-mentioned
meta-ML, that is, we machine learn best (initial) approaches, settings, defaults, and …

… Compared with other model markets, we present an open-source package manager for
machine learning. It has three main contributions and benefits to the MLOps ecosystem. • …

… novel features to perform population assignment using the concept and methods of machine
learning. It is a versatile r package in that it allows both genetic and non-genetic data to be …

ML4Chem is an open-source machine learning library for chemistry and materials science.
It provides an extendable platform to develop and deploy machine learning models and …

… Machine learning plays a major role in many scientific investigations. However, non-expert …
We introduce exprso, a new R package that is an intuitive machine learning suite designed …

… illustrate its usage in combination with the machine learning R package mlr (Bischl et al. …
package allows R users to easily search, download and upload data sets and machine learning …