README.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 (give at least 5 keywords / phrases).

Full text: [include a link that points to the full text of your thesis] Remark: a thesis is about research. We believe in the open science paradigm. Research results should be available to the public. Therefore, we expect dissertations to be shared publicly. Preferably, you publish your thesis via the edoc-server of the Humboldt-Universität zu Berlin. However, other sharing options, which ensure permanent availability, are also possible.
Exceptions from the default to share the full text of a thesis require the approval of the thesis supervisor.

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