Data Science - Computer Science - Machine Learning
With a strong foundation in Data and Computer Science, I'm adept at uncovering patterns in data, tackling algorithmic challenges, and crafting prediction models. If these are what you seek, then look no further.
- Data Analysis & Feature Design
- Web Mining & Fair Machine Learning
- Designing Prediction Models
- Mastery in Unsupervised, Semi-supervised, and Supervised Machine Learning
- Python expertise: Pandas, Numpy, Scikit-learn, Tensorflow, Keras, SciPy, and ChatGpt
- Scholarly Writing & Research
A testament to my academic prowess is the research paper I published titled "A method and analysis of predicting building material U-value ranges through geometrical pattern clustering" in the Journal of Building Engineering.
Open communication is paramount in every project. I welcome any questions about my expertise or background.
If you have a project that aligns with my skills, don't hesitate to reach out. I'm here to help!
Simon is the greatest option to work with, very efficient, smart, quick and very good in his area, he has gone above and beyond with this project and exceeded my expectations immensely. Quick answers and always with the solution of your problem.
*Time Series Analysis
RWTH Aachen university
Apr 2021 - Aug 2021 (4 months, 2 days)
* Revising and rewriting lecture material for the lecture Social data science
* Topics covered were data visualization, regression, causality, fair machine learning,
digital traces, crowdsourcing, and survey conduction
Jan 2021 - Aug 2021 (7 months, 1 day)
* Follow up job offered after finishing the Bachelor thesis
* Implementing and further improve the methodology developed in the thesis
* Gui development in Python with PySide
* Writing data transforming programs in Python to reduce workload
Highest possible level in every subject (oral interaction, reading, writing).
[...] analysis of predicting building material U-value ranges through geometrical pattern clustering
Journal of Building Engineering
The full title is "A method and analysis of predicting building material U-value ranges through geometrical pattern clustering".
The content can be summarized as applying machine learning techniques to initialize a digital model of a building for a calibration process.
Check https://orcid.org/0000-0003-1822-0020 for further information.