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Deep NLP Course at ABBYY

The crash course to the deep learning for NLP at ABBYY.

The textbook: Neural Network Methods in Natural Language Processing by Yoav Goldberg

Lecture Materials

Lecture 1: Introduction

A short overview of the most popular architectures in the deep learning.
A brief introduction into the keras framework.
Examples of models for sentiment analysis on the IMDB movie review dataset.
The Colab notebook.
Additional materials and deadlines.

Lecture 2: Fully-Connected Neural Networks and Word2Vec Models

An introduction into the PyTorch framework.
Example of a simple bag-of-words model for the sentiment analysis.
Examples of Word2Vec models: CBOW, Skip-Gram and Negative Sampling.
The Colab notebook.
Additional materials and deadlines.

Lecture 3: Recurrent Neural Networks, part 1.

A simple implementation of the vanilla RNN and an illustration of the vanishing gradient problem.
Examples of character-level LSTMs for:

  • Text classification: language prediction by the surname's spelling;
  • Conditional text generation: generation of the surname given language.

The Colab notebook.
Additional materials and deadlines.