https://github.com/amitrajitbose/lstm-time-series-viz

Visualizer for LSTM Network With Time-Series Data
https://github.com/amitrajitbose/lstm-time-series-viz

lstm-neural-networks tensorflow-experiments time-series

Last synced: 27 days ago
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Visualizer for LSTM Network With Time-Series Data

• Host: GitHub
• URL: https://github.com/amitrajitbose/lstm-time-series-viz
• Owner: amitrajitbose
• Created: 2019-05-03T17:58:47.000Z (over 5 years ago)
• Default Branch: master
• Last Pushed: 2019-05-11T17:15:47.000Z (over 5 years ago)
• Last Synced: 2024-09-27T21:03:22.472Z (about 1 month ago)
• Topics: lstm-neural-networks, tensorflow-experiments, time-series
• Language: Python
• Homepage:
• Size: 2.23 MB
• Stars: 9
• Watchers: 1
• Forks: 2
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Explore LSTM On Time Series Data (Without Any Code)

[![forthebadge made-with-python](http://ForTheBadge.com/images/badges/made-with-python.svg)](https://www.python.org/)

[![Generic badge](https://img.shields.io/badge/Status-Ready-Green.svg)](https://shields.io/)

---------------------------------------

     

![](http://www.microway.com/wp-content/uploads/TensorFlow_icon_180x148.png)

[![PyPI version](https://badge.fury.io/py/tensorflow-gpu%2F2.0.0a0.svg)](https://badge.fury.io/py/tensorflow-gpu%2F2.0.0a0)

# PoweredByTF 2.0 Challenge!

More news on [tensorflow.devpost.com](https://tensorflow.devpost.com/)

## Purpose

The sole purpose for the development of this software was to make it easy for learners to understand how tuning several hyperparameters can effect the result of an LSTM (Long Short Term Memory) network on various types of time series data.

## Dependencies

*   Python 3.x

*   Tensorflow

*   Matplotlib

## Running the App

*   Install `REQUIREMENTS.txt`, by running `pip install -r REQUIREMENTS.txt`

*   Open ``` app.py ``` file

*   Set the hyperparameter values ( **Dropout, Lag, Test Ratio, Max Epoch** )

*   Select a preloaded dataset 

*   Click ``` Start ```

*   To reset the console click ``` Reset ```

## OS Support

The application has been tested on Windows and Linux platforms. In case of any issue, feel free to raise an [issue](https://github.com/amitrajitbose/lstm-time-series-viz/issues/new).

## Examples

####    Increasing Sales dataset

     

####    Sinusoidal Curve Dataset

     

## Model Architecture

```

Model: "sequential"

_________________________________________________________________

Layer (type)                 Output Shape              Param #   

=================================================================

unified_lstm (UnifiedLSTM)   (None, LAG-1, 30)             3840      

_________________________________________________________________

dropout (Dropout)            (None, LAG-1, 30)             0         

_________________________________________________________________

unified_lstm_1 (UnifiedLSTM) (None, 30)                    7320      

_________________________________________________________________

dense (Dense)                (None, 1)                     31        

=================================================================

Total params: 11,191

Trainable params: 11,191

Non-trainable params: 0

_________________________________________________________________

None

```

## Preloaded Datasets

Currently, the application supports 5 different datasets. We are going to add more datasets and probably improve the model in the next iteration of development. Contributions are welcomed.

- Sine Wave

- Cosine Wave

- Increasing Sales

- Decreasing Sales

- Random Data

## Developers

`Amitrajit Bose` + `Anirban Mukherjee`