https://github.com/rouseguy/DeepLearning-NLP
Introduction to Deep Learning for Natural Language Processing
https://github.com/rouseguy/DeepLearning-NLP
Last synced: 3 months ago
JSON representation
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 (almost 9 years ago)
- Default Branch: master
- Last Pushed: 2020-05-26T20:10:55.000Z (about 5 years ago)
- Last Synced: 2025-03-28T22:12:30.496Z (3 months ago)
- Language: Jupyter Notebook
- Size: 13 MB
- Stars: 603
- Watchers: 33
- Forks: 211
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
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)