On the first episode we talked with Yoav Goldberg from Bar Ilan university about NLP, deep learning research, life in academia and that medium blog post that started a fire.
Opening tone: Avishai Cohen - Etzion Gever
More resources on this episode-
Yoav Goldberg is an NLP (Natural Languahe processing https://en.m.wikipedia.org/wiki/Natural_language_processing) researcher at Bar Ilan University, his official web page - http://u.cs.biu.ac.il/~yogo/.
The blog post Yoav Golberg published about the paper "adversarial generation of natural language" - https://firstname.lastname@example.org/an-adversarial-review-of-adversarial-generation-of-natural-language-409ac3378bd7 and the original paper https://arxiv.org/abs/1705.10929 which was publish in arxiv https://arxiv.org/.
We've discussed the application of neural network models (Deep learning) to natural language data, here is a primer about this by Yoav Goldberg http://u.cs.biu.ac.il/~yogo/nnlp.pdf and the book Yoav wrote - http://www.morganclaypoolpublishers.com/catalog_Orig/product_info.php?cPath=22&products_id=1056. In this context we've mentioned RNN (Recurrent neural network) and LSTM (Long Short Term Memory networks) - here is a nice blog post to understand these http://colah.github.io/posts/2015-08-Understanding-LSTMs/.
We've also mentioned in the episode SVM and kernels https://en.wikipedia.org/wiki/Kernel_method and this is an easy way to apply it with Python using scikit-learn library http://scikit-learn.org/stable/auto_examples/svm/plot_svm_kernels.html.
Yoav and his team developed a great Python library for deep learning in Python - Dynet - Dynamic Neural Network Toolkit https://github.com/clab/dynet. Other popular libraries for deep learning in Python are Tensorflow (developed by Google research https://www.tensorflow.org/) and Pytorch (developed by Facebook research http://pytorch.org/).