https://github.com/rouseguy/DeepLearning-NLP

Introduction to Deep Learning for Natural Language Processing
https://github.com/rouseguy/DeepLearning-NLP

Last synced: 11 days ago
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Introduction to Deep Learning for Natural Language Processing

• Host: GitHub
• URL: https://github.com/rouseguy/DeepLearning-NLP
• Owner: rouseguy
• License: mit
• Created: 2016-07-20T03:03:42.000Z (over 8 years ago)
• Default Branch: master
• Last Pushed: 2020-05-26T20:10:55.000Z (over 4 years ago)
• Last Synced: 2024-08-02T14:10:43.547Z (4 months ago)
• Language: Jupyter Notebook
• Size: 13 MB
• Stars: 605
• Watchers: 34
• Forks: 212
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Introduction to Deep Learning for Natural Language Processing

This repo accompanies the *Introduction to Deep Learning for Natural Language Processing* workshop to explain the core concepts of deep learning with emphasis on classifying text as the application. `Python` data stack is used for the workshop. 

 

## Overview

The following topics are covered

1. What is deep learning?

2. Motivation: Some use cases 

3. Building blocks of Neural Networks (Neuron, Activation Function, Backpropagation Algorithm)

4. Word Embedding

5. `word2vec`

5. Introduction to `keras`

6. Multi-layer perceptron

7. Convolutional Neural Network

8. Recurrent Neural Network

9. Challenges in Deep Learning

Depending on time, the following topics might be covered

1. Using `tensorflow` as backend for `keras`

2. Unsupervised learning using Autoencoders

 

## Installation Instructions

Please refer to the [installation](installation.md) instructions document. That document also has instructions on how to run a script to check if the required packages are installed. 

## Slides

The slides used for the workshop are available [here](https://speakerdeck.com/bargava/introduction-to-deep-learning-for-natural-language-processing)