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deeplearning

We're doing a biweekly study group about Deep Learning in Amsterdam: 1 evening (2-3h) every other week. It's for a group of people with strong CS + LA background, pref. some familiarity with machine learning and neural network basics.

Syllabus

Session Date Theory Coding
week 1 2016-09-18 intro talk, NN&DL ch1 ch1 coding assignments
week 2 2016-10-02 NN&DL^ ch2 webcam demo
week 3 2016-10-16 NN&DL^ ch3 sk-learn neural nets
week 4 2016-10-30 NN&DL^ ch4 + ch5 intro TensorFlow
week 5 2016-11-13 NN&DL^ ch6 TensorFlow (part 2)
week 6 2016-11-27 discussion TensorFlow (projects)
week 7 2016-12-11 DL$ ch10, RNNs, papers TensorFlow (projects)
week 8 2016-12-25 (skip)
week 9 2017-01-08 DL$ ch11, papers run existing projects
week 10 2017-01-22 DL$ ch12 (apps), papers Projects show-off, cocktails

^ [book] Neural Networks and Deep Learning, by Michael Nielsen

$ [book] Deep Learning, by Goodfellow, Bengio and Courville (full reading notes)

Resources

syllabus, proposal: practical approach, but with deep understanding (not just trying github repos): book Nielsen (ML -> DL), then a course (either Google, creative DL, or (outdated) coursera) with corresponding homeworks. Extra: papers (DL classics, microsoft ebook, IBM watson, DeepMind), practical DL projects (TensorFlow, Theano, Torch, Keras.io), deep dreaming, GPU programming

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