Machine Learning (ML) and Artificial Intelligence (AI) in Production

Motivation

Traditional ML pipeline design typically requires ML experts, which are rare and costly. To improve the availability of ML and enable its economic potential, automated machine learning (AutoML) frameworks have been developed. Companies, especially in production, often need tools that do not require massive programming skills, that produce results quickly, where problem solving is agile, and that are also applicable to production managers.

Description

In this seminar, benefits of AutoML systems are presented and when AutoML systems can be applied in production. Based on introductions into the topic ML and AI, its tools and methodologies, ML models are implemented manually. Then, AutoML tools are benchmarked with the manual implementation and influencing factors on the performance of AutoML tools are discussed. Finally a tool for selecting the right AutoML tool will be presented.

Goals

Enable you as a company to understand how and when to use AutoML systems, gain experience in using AutoML tools and increase model performances and decrease time for creating ML pipelines.