README_template.md

Title

Type: Master's Thesis / Bachelor's Thesis

Author: xxx

Supervisor: xxx (only if different from the 1st or the 2nd Examiner)

1st Examiner: xxx

2nd Examiner: xxx

[Insert here a figure explaining your approach or main results]

Table of Content

• Summary
• Working with the repo
  • Dependencies
  • Setup
• Reproducing results
  • Training code
  • Evaluation code
  • Pretrained models
• Results
• Project structure

Summary

(Short summary of motivation, contributions and results)

Keywords: xxx (please name at least 5 keywords / phrases).

Working with the repo

Dependencies

Which Python version is required?

Does a repository have information on dependencies or instructions on how to set up the environment?

Setup

[This is an example]

1. Clone this repository

2. Create an virtual environment and activate it

python -m venv thesis-env
source thesis-env/bin/activate

3. Install requirements

pip install --upgrade pip
pip install -r requirements.txt

Reproducing results

Describe steps how to reproduce your results.

Here are some examples:

• Paperswithcode
• ML Reproducibility Checklist
• Simple & clear Example from Paperswithcode (!)
• Example TensorFlow

Training code

Does a repository contain a way to train/fit the model(s) described in the paper?

Evaluation code

Does a repository contain a script to calculate the performance of the trained model(s) or run experiments on models?

Pretrained models

Does a repository provide free access to pretrained model weights?

Results

Does a repository contain a table/plot of main results and a script to reproduce those results?

Project structure

(Here is an example from SMART_HOME_N_ENERGY, Appliance Level Load Prediction dissertation)

├── README.md
├── requirements.txt                                -- required libraries
├── data                                            -- stores csv file 
├── plots                                           -- stores image files
└── src
    ├── prepare_source_data.ipynb                   -- preprocesses data
    ├── data_preparation.ipynb                      -- preparing datasets
    ├── model_tuning.ipynb                          -- tuning functions
    └── run_experiment.ipynb                        -- run experiments 
    └── plots                                       -- plotting functions