Machine Learning for Engineers in MATLAB

We explore the innovative integration of machine learning in chemical engineering education. The focus is on the "Machine Learning for Engineers" course, which has been translated from Python into MATLAB. This initiative addresses the growing interest in machine learning within the chemical engineering sector to equip students with relevant skills in this rapidly evolving domain. The webinar covers the development and use of comprehensive course modules, now accessible on GitHub and File Exchange (github.com/APMonitor/mds). These modules, suitable for both instructor-led and self-paced learning, encompass a broad range of topics including additive manufacturing, concrete strength, lithium-ion batteries, and polymer analysis among the 36 learning modules and 18 case studies.
The webinar also covers the pedagogical approach and resources in this course. Emphasis is placed on user-friendly app-based workflows in MATLAB and Live Scripts to lower the learning barriers for students and instructors. The dual-language structure of the course, with both MATLAB and Python, is designed to enhance programming skills and offer a comprehensive understanding of machine learning applications in chemical engineering. Participants gain insights into the practical applications of machine learning in industry with fundamental understanding of the algorithms with physics-informed feature selection. This webinar is for educators and professionals to deepen understanding of the role of machine learning in chemical engineering and discover resources that can be directly applied to enhance curricula or professional practice.

[@dr.alikhudhair9414]

Wonderful .. Great thank professor

[@hubstrangers3450]

Thank you......

[@IndustryProspect]

Clean as f