Deep Learning
In the last ten years there has been a revolution in the field of Artificial Intelligence, mainly
as the result of the revival of an approach called "Deep Learning". Deep
Learning is the subfield of Machine Learning which is based
on Artificial Neural Networks with many "layers".
The Deep-Learning course gives an overview over the main ideas and techniques of Deep
Learning and explains the practical implementation of Deep Learning algorithms using Python & Keras
in detail. At the end of the course participants will be
able to program state of the art algrithms in computer vision with a few lines of code.
The course assumes familiarity with core Python and also some basic knowledge of Linear Algebra, Calculus, and Probability Theory. The topics covered are:
- Introduction to the theory of Artificial Neural Networks (ANNs)
- Introduction to Keras
- Practical Exercises: Construction & Training of ANNs (with Keras, using the TensorFlow backend)
- Introduction to Convolutional Neural Networks (CNNs)
- Practical Exercises: Applications of CNNs to Computer Vision Tasks (with Keras)
- Selected topics from general Machine Learning, including a very gentle introduction to Feature/Representation Learning and to Generalization Theory.
The standard course duration is 2 days. On request, this course can be combined with one of the other courses with a duration between 2 and 5 days.