https://github.com/danielprasetyo7952/tugas-akhir

Documentation of thesis on Foreign Exchange Forecasting with LSTM and Genetic Algorithm
https://github.com/danielprasetyo7952/tugas-akhir

genetic-algorithm lstm streamlit tensorflow

Last synced: 4 days ago
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Documentation of thesis on Foreign Exchange Forecasting with LSTM and Genetic Algorithm

• Host: GitHub
• URL: https://github.com/danielprasetyo7952/tugas-akhir
• Owner: danielprasetyo7952
• License: mit
• Created: 2023-05-04T17:28:00.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2024-08-21T06:14:02.000Z (3 months ago)
• Last Synced: 2024-08-21T07:39:02.851Z (3 months ago)
• Topics: genetic-algorithm, lstm, streamlit, tensorflow
• Language: Jupyter Notebook
• Homepage: https://tugas-akhir-preview.streamlit.app/
• Size: 52.5 MB
• Stars: 3
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Tugas Akhir

This repository that contains documentation of my thesis on **Foreign Exchange Forecasting**. This repository serves as a record of the work that has been done and provides valuable insights into the methods and techniques used in the thesis.

## Methods

Methods that are implemented in the thesis:

- LSTM Model

- Genetic Algorithms for Optimization

## Usage

1. To use this repository, simply clone it to your local machine

2. Install the dependencies from `requirements.txt` file with `pip install -r requirements.txt`

3. After all dependencies are installed, you can run the notebook

**Note :**

It should be noted that I am using **Python Version 3.10**, so if some dependencies cannot be installed then you should install **Python Version 3.10**

## Future Plan

- [x] Use Streamlit to create the model GUI -- [Repository](https://github.com/danielprasetyo7952/Tugas-Akhir-Preview)