The goal of this session is to give participants a better insight into the type of problems that can be tackled using machine-learning techniques, illustrated by several real-world examples from a diverse set of domains. Among others, the following machine-learning methodologies will be covered:
- Reinforcement learning
- Deep learning
- Evolutionary algorithms
- Transfer learning
For each method, its characteristics, advantages and disadvantages will be explained in more detail, as well as the most commonly used algorithm(s) to solve a particular industrial problem. The aim is to guide the participants in making a conscious choice for the appropriate technique in function of the problem setting at hand, as well as the available data (dimensionality, attribute types, etc.) and the expected model requirements (interpretability, accuracy, scalability, etc.).
Sirris, Gaston Geenslaan 8, 3001 Heverlee
Price and conditions
- Normal price: 625 EUR
- Early Bird* or Sirris Member**: 575 EUR
- All prices are exclusive of VAT
- A hardcopy of the course notes is included in the registration price. All sessions are given in English.
*Non-Sirris members registering more than 3 weeks in advance, benefit from the Early Bird price.
**This price is applicable for any Sirris member who subscribes at any time.
If you are a Flemish SME you can also make use of the kmo-portefeuille (the kmo-portefeuille should be requested at latest 14 days after the course has taken place). (Erkenningsnr. Sirris: DV.O105154). Please note that if you do not apply in time your request will be declined.
Our general terms and conditions
Any cancellation has to be made by e-mail (email@example.com). Cancellations made before the 3 business days preceding a session are free of charge. After this deadline, 50% of the participation fee will be charged (incl. VAT). In case of cancellation the day itself, the full amount of the registration will be due. In case of 'no-show' the full amount of the registration fee will be due too. Replacement by a colleague is always possible if notified in advance by e-mail (firstname.lastname@example.org).