Project Report Template

This repository serves as a template for your project reports as part of the Document Analysis lecture. To set up your project report as a webpage using GitHub Pages, simply follow the steps outlined in the next chapter.

Some Organizational Details: Get creative with your project ideas! Just make sure they relate to Natural Language Processing and incorporate this specified dataset: Link to data, Link to paper. Submissions should be made in teams of 2-3 students. Each team is expected to create a blog-style project website, using GitHub Pages, to present their findings. Additionally, teams will deliver a lightning talk during the final lecture to discuss their project. Add all your code, such as Python scripts and Jupyter notebooks, to the code folder. Use markdown files for your project report. Here you can read about how to format Markdown documents.

Have fun working on your project! 🥳

Setup The Report Template

Follow this steps to set up your project report:

Fork the Repository: Begin by creating a copy of this repository for your own use. Click the Fork button at the top right corner of this page to do this.
Configure GitHub Pages: Navigate to Settings -> Pages in your newly forked repository. Under the Branch section, change from None to master and then click Save.
Customize Configuration: Modify the _config.yml file within your repository to personalize your site. Update the title: to reflect the title of your project and adjust the description: to provide a brief summary.
Start Writing: Start writing your report by modifying the README.md. You can also add new Markdown files for additional pages by modifying the _config.yml file. Use the standard GitHub Markdown syntax for formatting.
Access Your Site: Return to Settings -> Pages in your repository to find the URL to your live site. It typically takes a few minutes for GitHub Pages to build and publish your site after updates. The URL to access your live site follows this schema: https://<<username>>.github.io/<<repository_name>>/

Project Title

Group members: Name 1, Name 2, Name 3

Introduction

Start off by setting the stage for your project. Give a brief overview of relevant studies or work that have tackled similar issues. Then, clearly describe the main question or problem your project is designed to solve.

Dataset

Provide a short description of the dataset used in your project. Focus on highlighting the aspects that are particularly relevant to your work.

Methods

Setup

Outline the tools, software, and hardware environment, along with configurations used for conducting your experiments. Be sure to document the Python version and other dependencies clearly. Provide step-by-step instructions on how to recreate your environment, ensuring anyone can replicate your setup with ease:

conda create --name myenv python=<version>
conda activate myenv

Include a requirements.txt file in your project repository. This file should list all the Python libraries and their versions needed to run the project. Provide instructions on how to install these dependencies using pip, for example:

pip install -r requirements.txt

Experiments

Report how you conducted the experiments. We suggest including detailed explanations of the preprocessing steps and model training in your project. For the preprocessing, describe data cleaning, normalization, or transformation steps you applied to prepare the dataset, along with the reasons for choosing these methods. In the section on model training, explain the methodologies and algorithms you used, detail the parameter settings and training protocols, and describe any measures taken to ensure the validity of the models.

Results and Discussion

Present the findings from your experiments, supported by visual or statistical evidence. Discuss how these results address your main research question.

Conclusion

Summarize the major outcomes of your project, reflect on the research findings, and clearly state the conclusions you've drawn from the study.

Contributions

Team Member	Contributions
Alice Smith	Data collection, preprocessing, model training, evaluation
Bob Johnson	...
...	...

References

Include a list of academic and professional sources you cited in your report, using an appropriate citation format to ensure clarity and proper attribution.

julianschelb/awesome-project