Introduction to Machine Learning for Simulation Engineers and Scientists
Course Objective:
Data Analytics provides the technology to build data-driven predictive models and to search for interesting patterns in large amounts of data. At the core of data analytics lays the field of Machine Learning, which provides all the conceptual infrastructure and algorithms to build computer systems that learn from experience. Machine Learning is a subfield of Artificial Intelligence; it has received unprecedented attention lately due to its use in many real-world applications.
The course will explain how to build systems that learn and adapt borrowing from examples in industry and science, e.g.
- learning to predict medical diagnoses,
- anticipating machine failures,
- minimizing the cost of expensive simulations
- neural networks
- deep learning
- decision trees
- unsupervised learning
- ensemble methods
- application of ML to FEA
- This course is recommended for everyone interested in machine learning and its application in science and engineering.
This course is available on request. If you are interested in this course, please send us an email to [email protected]