Lectures and corresponding seminars are in the ./day* folders.
Useful links:
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day 0 morning Recap
- Lecture: Linear models, stochastic optimization, regularization
- Seminar: Adaptive optimization methods for subgradient SVM
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day 0 afternoon Going deeper
- Lecture: Neural networks 101
- Seminar: theano, symbolic graphs and basic neural networks
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day 0 evening Yandex/HSE introductory note
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day 1 morning Vision & convolutional networks
- Lecture: Computer vision problems. Convolutional neural networks. Tips and tricks. Fine-tuning.
- Seminar: lasagne and CIFAR
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day 1 afternoon Natural language processing & embeddings
- Lecture: NLP problems and applications, bag of words, word embeddings, word2vec, text convolution.
- Seminar: Embeddings and text convolutions for salary prediction.
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day 1 evening Generative adversarial networks
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day 2 morning Recurrent neural networks for sequences
- Lecture: Sequence modelling. Simple RNN. BPTT. Gradient vanishing/explosion. LSTM/GRU. Grad clipping.
- Seminar: Generating names & modecules with recurrent neural networks
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day 2 afternoon Connecting it all together: image captioning
- Lecture: RNN as Encoder/Decoder/Seq2seq. Common semantic space. Image captioning.
- Seminar: Image captioning
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day 2 evening Outro
Course staff
Contributors
- Arseniy Ashukha - image captioning, sound processing, week7&9 lectures
- Oleg Vasilev - seminars here and there
- Vadim Lebedev - seminar for linear models.
The course is based on our HSE_deepelarning track.