- Workshop Date: Sunday 18th of June
- Workshop Starting Time: 10:00 AM
- Participants Limit: 70
- Workshop Coordinator: Prof Antonio Rio
a.del-rio-chanona@imperial.ac.uk
Registration Link: https://era.eventsair.com/escape-33/workshops
Machine Learning Workshop
Machine Learning Workshop
This workshop will provide a comprehensive introduction to various machine learning models, such as neural networks, decision trees, radial basis functions, and Gaussian processes. Participants will gain a solid understanding of these models, including their practical applications, underlying theories, training techniques, best practices, and their relevance to the fields of chemical and process engineering.
In addition, the workshop will delve into the realm of data-driven optimization, where machine learning models play a crucial role in the optimization process. Participants will explore different algorithms (e.g Bayesian optimization, ENTMOOT), and learn about their applications in the field of chemical engineering.
Building on the above, the workshop will cover dynamic systems, time series analysis, control systems, and sequential decision-making problems. Participants will discover how machine learning can be effectively employed to address these challenges. Specifically, they will explore topics such as data-driven model predictive control and reinforcement learning. Reinforcement learning, for instance, is the technique that enabled machines to surpass human players in complex games like Go and chess, and it played a key role in the development of ChatGPT.
By attending this workshop, participants will gain insights into the theory and practical implementation of machine learning models, empowering them to address real-world and research problems.
Content:
- What is Machine Learning?
- Machine Learning models
- Data-driven optimization
- Data-driven sequential decision making: Reinforcement Learning and Data-driven Model Predictive Control
