What you will learn
- How Machine Learning works, its possibilities, its limitations, and the importance of data
- How to create, evaluate and deploy predictive models, via open source libraries, APIs and ML-as-a-Service platforms
- How to formulate ML problems that create value from data and that power predictive applications with innovative features
See workshop agenda for more details.
- Experience in programming and with the command line
- Attendees are expected to bring their own laptops for the hands-on practical work
- Basic knowledge of calculus, linear algebra, and probability theory will be useful for Theory in Modules 2, 4, 5 (see agenda)
This course is targeted to hackers, developers, software engineers and CTOs who are beginners in machine learning.
Each workshop will be given in a classroom setting with up to 20 participants.
Join now to avoid missing out!