The course consists of five days (Mon-Friday) of lectures and exercises on key topics in machine learning. This years summer school will focus on deep learning. The course (2.5 ects point) is passed by handing in a small report on one of the topics covered in the course on deep learning. The exercises cover both theoretical, technical programming and application aspects. It will be up to the students to decide on what aspects to focus on in the report. Specific machine learning application examples are used throughout the entire week. For further course details click here.
Technical University of Denmark, DTU Compute, Building 324 rooms 040 and 060
9AM-5PM every day August 24th-28th, 2015
Lectures will be given by invited speakers and staff at the Section for Cognitive Systems.
General understanding of machine learning, statistical modeling, mathematics and computer science. For the course you are required to bring your own laptop computer. The course will use Python, Theano and Lasagne. We highly recommend to go through the installation guide at the end of the course program and install this required software before the course.
Lars Kai Hansen
Introduction to Neural Networks
Introduction to GPU programming
Anders Boesen Lindbo Larsen
Convnets: Power tools for your computer vision toolbox
Recurrent Neural Networks
Probability & Neural Networks
Combining Supervised and Unsupervised Learning (and the Ladder Network)
Machine learning for image editing
Registration is at this point closed. As we anticipate more applicants than we have space for applicants will be selected based on their curriculum vitae (CV). To register please send an email to Wanja Andersen firstname.lastname@example.org with your CV (maximum 2 pages). The CV has to be received no later than 14th of June. We will notify applicants regarding acceptance to the summer school 19th of June.
For academics (masters and PhD students) there is no registration fee for the course. For all other participants a course fee of DKK 8250 will be charged. Participants are to cover all other costs such as food, accommodation, and travel expenses.
For practical information regarding transportation and accommodation click here.
2014 version of 02901 Advanced Topics in Machine Learning
For further information, please contact: