Neural Networks and Deep Learning, and Deep Learning by Goodfellow/Bengio/Courville. Both books are available online.Also look at the DeepMind course on deep learning, available here.
Every research seminar session includes a short discussion about the NN projects that students are undertaking.
On Tuesdays we will typically do research seminars, and round-tables on Thursdays.
This week we do course planning and round-table all week
Tuesday: Discussion of the NN package we will use
Thursday: special session on variational inference for Bayesian models
ch. 4, ch. 5, ch. 6
Tuesday: General discussion about research methods
A primer on neural network models for Natural Language Processing
For those writing a course paper / second year paper with Katrin: Course paper proposal due Tuesday Mar 21: 1-2 pages, outline of what you are planning do to
Goodfellow/Bengio/Courville ch. 6: Deep Feedforward Networks.
Tuesday: We finish our discussion of Levy/Goldberg and of the GloVe paper.
We also read, on autoencoders and recursive neural networks:
Additional readings that we will not discuss in class:
If you would like a more in-depth understanding of restricted Boltzmann machines, Su recommends Fischer and Igel, an Introduction to Restricted Boltzmann machines.
We discuss, on autoencoders and recursive neural networks:
For those writing a course paper / second year paper with Katrin: Course paper intermediate report due Tuesday April 11: 2-3 pages, extension of the course proposal document, updated to take comments into account and updated by your progress to date
Tuesday: LSTMs, Long Short Term Memory networks:
Tuesday: We talk about attention. Readings from the Deepmind course on deep learning:
Optional reading: On this day, Su also talks about GANs. His tutorial is here.
Tuesday: Extended round table.
For those writing a course paper / second year paper with Katrin: Course paper final version due date : Thursday May 4. Please submit 8-10 pages, building on the progress report you submitted.