Skip to content

Latest commit

 

History

History
62 lines (51 loc) · 2.86 KB

README.md

File metadata and controls

62 lines (51 loc) · 2.86 KB
Raw

Prediction of Metal Coating Properties for Greener Air Travel

The report for this study can be found here.

User Manual

Cloning of this Repository on Github

  • Using the Command Line Tool in your desired IDE, run:

      git clone https://github.com/liewyihseng/20090325_submission.git

  • This will allow the latest version of source code to be cloned into the workspace.

  • If you are facing any issue on cloning this file, do drop me an email at [email protected] as this repository is currently still in private mode.

Importing of Anaconda Environment

  • Have Anaconda Navigator opened in your machine.
  • Head to the Environments tab on the most left part of the window.
  • Search for 'Import' that lies at the bottom left part of the window.
  • At the 'Local Drive', simply insert the path that directs to environment.yml file within the cloned repository.
  • Simply assign a name for the new environment and remember to check the 'Overwrite existing enironment' checkbox.
  • After that, simply select 'Import'.
  • The process of importing the environment might take awhile, please be patient.
  • If you have followed the steps, the designated environment with the environment name you have specified has been imported.

Prerequisites

Installation of Git

  • Go to this link: https://git-scm.com/download/win.
  • Select the version based on your machine's information.
  • Extract the files followed by running of the installer.

Installation of Anaconda

Installation of Anaconda can be accessible through this link : https://docs.anaconda.com/anaconda/install/windows/

Running of Source Code

  • After having all the prerequisites done, you are now ready to run the cloned source code.
  • Go to Anaconda Navigator and head to the environment tab on the most left part of the window.
  • Search for the environment you have imported and click onto the start icon beside the enviroment to boot up the environment.
  • Simply head to Home tab and search for Jupyter Notebook.
  • Select 'Launch' to have Jupyter Notebook booted up.
  • Within Jupyter Notebook, head to directory containing the repository.
  • Click on the files you would like to access.
  • To run the Machine Learning technique training, click on the run all symbol in the navigation bar.
  • The training will automatically start where a series of output will be presented.

Python Version

The project within this repository utilises Python 3.7.11

Attribute

All files included inside the lib folder are written in-house.

List of packages (Standard Libraries) that has been included into the project are as follow:

  • notebook: 6.4.8
  • keras: 2.4.3
  • keras_tuner: 1.1.0
  • matplotlib: 3.4.3
  • numpy: 1.20.3
  • pandas: 1.3.4
  • scikit-learn: 0.24.2
  • scipy: 1.7.3
  • tensorboard: 2.6.0
  • tensorflow: 2.3.0