Skip to content

Contains different course tutorials and jupyter notebook file for applying different Deep Learning models in different NLP tasks such as text classification, summarization, translation, etc.

Notifications You must be signed in to change notification settings

snrazavi/Deep-Learning-for-NLP

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

32 Commits
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Deep-Learning-for-NLP

Contains different course tutorials and jupyter notebook file for applying different Deep Learning models in different NLP tasks such as text classification, summarization, translation, etc.

Contents

1. Introduction

  • basic concepts
  • Text representation, BoW, Word vectors

2. Text classification and Sentiment Analysis

  • Naive Bayes
  • Logistic Regression
  • fastText model
  • Deep models
    • RNNs and LSTMs
    • Convolutional neural networks for text classification
    • RCNN (Recurrent convolutional neural networks for text classification
    • AWD LSTMs and ULFiT approach
    • Transformers (Bert, XLNet, etc.)

3. Neural Machine Translation

4. Text summarization

5. Other NLP tasks

Getting started

Reference

About

Contains different course tutorials and jupyter notebook file for applying different Deep Learning models in different NLP tasks such as text classification, summarization, translation, etc.

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published