Data preprocessing is a crucial step in any machine learning (ML) pipeline, as the quality of
the data can greatly impact the accuracy and effectiveness of the final model. With the rise of …

Abstract Machine learning (ML) has become a vital part in many aspects of our daily life.
However, building well performing machine learning applications requires highly …

An important turning point in the field of machine learning has been reached with the
convergence of data preparation and automated machine learning (AutoML). AutoML has …

This thesis focuses on data preprocessing as one crucial step of Automated machine
learning (AutoML). Investigation of data preprocessing of the current stateof-the-art methods …

Automate data and model pipelines for faster machine learning applications Key Features
Build automated modules for different machine learning components Understand each …

There has been considerable growth and interest in industrial applications of machine
learning (ML) in recent years. ML engineers, as a consequence, are in high demand across …

Abstract Automated Machine Learning (AutoML) has emerged as a powerful paradigm to
streamline the process of building and deploying machine learning models by automating …

This thesis focuses on data preprocessing as one crucial step of Automated ma chine
learning (AutoML). Investigation of data preprocessing of the current stateof-the-art methods …

Machine learning (ML) is used in many applications but creating a useful model from data is
a knowledge-intensive and laborious task. Automated machine learning (AutoML) aims to …

This paper presents a comprehensive exploration of automatic machine learning (AutoML)
tools in the context of classification and regression tasks. The focus lies on understanding …