Machine Learning – from Zero to Hero
2022, Mar 02
This course aims to give deep knowledge about Machine Learning (ML):
- What it is.
- What it is not.
- When to apply it.
- How to apply it.
Upon completion of the course, the user should be comfortable in training and applying ML.
- The course covers every stage of the Data Science Lifecycle, including verification & validation of ML.
- Learn how to put Machine Learning into practice and how to verify your Machine Learning solution.
- Apply ML in practice, both virtually and on embedded target environment.
During the course, the participants will be able to practice on all steps necessary to train, test (verify), integrate (on HW), and validate a machine learning model.
The exercises will be split over the two days. The first day covers exercise setting up the workflow and training an initial model and the second day handles testing and deployment. After completing the course, each participant will be allowed to bring home the Raspberry Pi containing their trained and tested model.
Course content
- Introduction to AI/ML
- Development environment
- Selection of algorithm and training
- Data management
- Verification & Validation of ML functionality
- Apply ML in practice, both virtually and on embedded target environment
- Risks surrounding the use of ML
Links
Machine Learning – from Zero to Hero