top of page

My data highlights

Updated: May 1, 2023

Over the years I had the opportunity to work on multiple data driven projects. I learned a lot across different industries and data challenges. Here's an overview of my highlights. Some projects involve confidential client data, so I cannot publish the code nor dig deeper in the solution. For transparency, some of them are personal projects or something I did in an (unpaid) partnership for my University. These will be explicitly mentioned as [Unremunerated]. Even in this case, I am only publishing the GitHub repository and dataset of the ones that used exclusively public datasets.


Last but not least: I would like to thank all the partners for their time, commitment and of course data. These projects are my highlight not only because of the results, but also because I enjoyed working on them.

 

Customer satisfaction Text Analysis (2022)

Partner: EY Netherlands, for ***

Industry: Healthcare

Dataset: Interviewing text data, with multiple questions

Goal: Understanding the insights in the data

Challenge: ***

Solution: ***

Tool: Spacy, EmoRoberta, Sumy, LDA (Python)

Analysis of facilities blind spots in the Netherlands (2022)



Analysis of road traffic accidents in the UK (2022)

Partner: Technische Universiteit Eindhoven (University project) [Unremunerated]

Industry: Automobile, Public affairs

Dataset: Public Data of road traffic accidents in the UK

Goal: Improving Road Safety

Challenge: Making it as interative and intuitive as possible

Solution: The tool can be accessed at https://github.com/octokami/uk_road_safety

Tool: Dash (python)




Stock prediction from news articles (2022)

Partner: Technische Universiteit Eindhoven [Unremunerated]

Industry: Financial, Publishing

Dataset: Stock Values from Yahoo and News from Kaggle

Goal: Evaluating the effect of sentiment in news about a company in their performance in the stock market.

Challenge: It is difficult to disassociate the external factors.

Solution: https://github.com/octokami/news_stock_market

Tool: GaussianNB (Python)


Breast cancer 3D model prediction (2021)

Parking peak hours prediction (2021)

Supermarket stock forecast (2019): Bachelor thesis project

Data integration and analysis (2019)


56 views0 comments

Commentaires

Noté 0 étoile sur 5.
Pas encore de note

Ajouter une note
bottom of page