https://github.com/omerbsezer/basiclstm

The aim of this implementation is to help to learn structure of basic LSTM (LSTM cell forward, LSTM cell backward, etc..)
https://github.com/omerbsezer/basiclstm

deep-learning lstm-neural-networks tutorial-code

Last synced: about 2 months ago
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The aim of this implementation is to help to learn structure of basic LSTM (LSTM cell forward, LSTM cell backward, etc..)

• Host: GitHub
• URL: https://github.com/omerbsezer/basiclstm
• Owner: omerbsezer
• Created: 2018-08-19T20:24:28.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2018-08-19T20:27:16.000Z (over 6 years ago)
• Last Synced: 2023-03-07T17:22:32.566Z (almost 2 years ago)
• Topics: deep-learning, lstm-neural-networks, tutorial-code
• Language: Python
• Size: 7.81 KB
• Stars: 3
• Watchers: 2
• Forks: 3
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Basic Long Short Term Memory (LSTM)

* Long Short Term Memory (LSTM) is a type of deep learning model that is mostly used for analysis of sequential data (time series data prediction). 

* There are different application areas that are used: Language model, neural machine translation, music generation, time series prediction, financial prediction, etc. 

* The aim of this implementation is to help to learn structure of basic LSTM (LSTM cell forward, LSTM cell backward, etc..).

* Code is adapted from Andrew Ng's Course 'Sequential models'.

## LSTM Cell



## LSTM Forward Pass



## Reference

* Andrew Ng, Sequential Models Course, Deep Learning Specialization