Topics:
- What is reproducible research?
- Reproducible research practices
- Project organisation for reproducible research
- Reproducible analyses
This course will span over two days. The second half will be on September 14 at 2 pm.
→ Register here ←
Topics:
- What is reproducible research?
- Reproducible research practices
- Project organisation for reproducible research
- Reproducible analyses
This is day two of the course starting on September 13 at 1 pm.
This course will introduce participants to the concepts of AI and Machine Learning, covering clustering and clasifications fundamentals as well as practical experience with standard methods for both techniques. Lastly, participants will gain an insight on best practises for evaluating a machine learning model's performance (ROC curve, FPR etc.)
More information can be found here:...
This is day two of the course starting on September 15 at 2 pm.
This course will introduce participants to the concepts of AI and Machine Learning, covering clustering and clasifications fundamentals as well as practical experience with standard methods for both techniques. Lastly, participants will gain an insight on best practises for evaluating a machine learning model's performance ...
This is an hands-on introduction to the first steps in Deep Learning, intended for researchers who are familiar with (non-deep) Machine Learning.
The use of Deep Learning has seen a sharp increase of popularity and applicability over the last decade. While Deep Learning can be a useful tool for researchers from a wide range of domains, taking the first steps in the world of Deep Learning...
This is an hands-on introduction to the first steps in Deep Learning, intended for researchers who are familiar with (non-deep) Machine Learning.
The use of Deep Learning has seen a sharp increase of popularity and applicability over the last decade. While Deep Learning can be a useful tool for researchers from a wide range of domains, taking the first steps in the world of Deep Learning...
Topics covered involve basic concepts in statistical learning, as well as supervised learning techniques (high-dimensional regression and classification) and unsupervised learning (mixture models and dimension reduction).
→ Register here ←
Topics covered involve basic concepts in statistical searning, as well as supervised learning techniques (high-dimensional regression and classification) and unsupervised learning (mixture models and dimension reduction).
This is day two of the course starting on September 21 at 2 pm.
During this course participants will get an introduction to the topic of Explainable AI (XAI). The goal of the course is to help participants understand how XAI methods can help uncover biases in the data or provide interesting insights. After a general introduction to XAI, the course goes deeper into state-of-the-art model agnostic interpretation techniques as well as a practical session...
