Summer Course in Dresden: Deep Learning with Keras -- apply now!

This hands-on course will take you from 0 to 100 in Deep Learning with Keras. Our aim is to teach the fundamentals of deep learning with Convolutional Neural Networks (CNN) based on modern techniques using the Keras API and the Tensorflow backend. By the end participants will know how to build deep learning models, how to train them, what to avoid during training, what to check during training and how to perform model inference, especially for image based problems. We hope participants will then go out and apply these methods to their own problems and use cases.

The core curriculum is planned from Tuesday (August 22) to Thursday night (August 24) to take place at the MPI CBG campus, Dresden, Germany. As the agenda is currently being prepared please check-in from time to time. There is the latent plan to have voluntary session before (introduction to python) and after the workshop (hackday to work on the challenges you have). This is why the workshop currently blocks the entire week.

All participants are expected to bring their laptop. During the workshop, a uniform access to GPU-enabled workstations or servers will be provided that hold the software stack used. Thus, your laptop is not required to hold a mobile GPU or alike. All participants are expected to have a solid understanding of fundamentals of linear algebra as well as programming.

The workshop admission fee amounts to € 100 per participant. Every successfull applicant is required to bring a poster to the workshop that describes their current scientific challenge that they would like to solve with Deep Learning. Posters have to be sent in 1 week prior to the workshop.

More information here:
(Apply here before 31 May 2017.)
EDIT: Apply here before 30 June 2017:

Note that we can only host up to 30 students. We will try to select the best fitting applicants based on their background and motivation. We are looking forward to see you in Dresden this summer!



Application deadline extended until the 30st of June 2017! Go for it!

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