**Table of Contents**

0:00 Generating the dataset for binary classification of parentheses

4:56 Elman network

11:25 RNN with gating

14:06 LSTM

18:33 Be careful with errors given on the training set!

notebook (or opened in colab) for predicting engine failure with RNN solution (forum login required)

Hewitt, J., Hahn, M., Ganguli, S., Liang, P., & Manning, C. D. (2020). RNNs can generate bounded hierarchical languages with optimal memory.arXiv:2010.07515

Machine translation

Sutskever, I., Vinyals, O., & Le, Q. V. (2014). Sequence to sequence learning with neural networks. In Advances in neural information processing systems (pp. 3104-3112).

Cho, K., van MerriÃ«nboer, B., Gulcehre, C., Bahdanau, D., Bougares, F., Schwenk, H., & Bengio, Y. (2014, October). Learning Phrase Representations using RNN Encoderâ€“Decoder for Statistical Machine Translation. In Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP) (pp. 1724-1734).

SketchRNN: RNN and VAE

Ha, D., & Eck, D. (2018, February). A Neural Representation of Sketch Drawings. In International Conference on Learning Representations.

Generating LaTeX code from handwritten maths

Zhang, J., Du, J., & Dai, L. (2017, November). A GRU-based Encoder-Decoder Approach with Attention for Online Handwritten Mathematical Expression Recognition. In 2017 14th IAPR International Conference on Document Analysis and Recognition (ICDAR) (Vol. 1, pp. 902-907). IEEE.

Solving mathematical expressions

Lample, G., & Charton, F. (2019, September). Deep Learning For Symbolic Mathematics. In International Conference on Learning Representations.