rouseguy / Deeplearning Nlp
Licence: mit
Introduction to Deep Learning for Natural Language Processing
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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
- What is deep learning?
- Motivation: Some use cases
- Building blocks of Neural Networks (Neuron, Activation Function, Backpropagation Algorithm)
- Word Embedding
word2vec- Introduction to
keras - Multi-layer perceptron
- Convolutional Neural Network
- Recurrent Neural Network
- Challenges in Deep Learning
Depending on time, the following topics might be covered
- Using
tensorflowas backend forkeras - Unsupervised learning using Autoencoders
Installation Instructions
Please refer to the installation 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
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