In recent years, an active field of research has developed around automated machine
learning (AutoML). Unfortunately, comparing different AutoML systems is hard and often …

Despite great successes in many fields, machine learning typically requires substantial
human resources to determine a good machine learning pipeline (including various types of …

Automated Machine Learning (AutoML) frameworks regularly use ensembles. Developers
need to compare different ensemble techniques to select appropriate techniques for an …

As data science becomes more mainstream, there will be an ever-growing demand for data
science tools that are more accessible, flexible, and scalable. In response to this demand …

Automated machine learning (AutoML) methods improve upon existing models by
optimizing various aspects of their design. While present methods focus on hyperparameters …

Automated Machine Learning (AutoML) is an upcoming field in machine learning (ML) that
searches the candidate model space for a given task, dataset and an evaluation metric and …

The abundance of interest in machine learning (ML) and its applications has caused many
breakthroughs over recent years. Translating texts, speech recognition, and image …

The pipeline optimization problem in machine learning requires simultaneous optimization
of pipeline structures and parameter adaptation of their elements. Having an elegant way to …

Atlantic is an open-source Python package designed to simplify and automate data
preprocessing for supervised ML (Machine Learning) tasks. The Atlantic package integrates …

Automated machine learning (AutoML) and artificial neural networks (ANNs) have
revolutionized the field of artificial intelligence by yielding incredibly high-performing models …