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Hi šŸ‘‹

  • šŸ”­ Iā€™m currently working on my master thesis on "ESG criteria quantification for the real estate market".
  • šŸŒ± Former classes: Foundations of Data Science, Computational Complexity, Computational Finance, Blockchains and Quantitative Risk Management, Applied Data Analysis, Markov Chains, Scala, Machine Learning, Stochastic Calculus and Finance, Database Systems (SQL), Advanced Algorithms, Derivatives, Data visualization, Optimization for ML, Large-scale data science for real-world data and Signal processing.
  • āš” Number of plants in my room: 14.

Top Langs

My GitRepos:

Topic Repository Link Technology
Data Analysis Semester Project on migration modelling Python Pandas scikit-learn
ML Classification of ordinal outcomes for the analysis of injury severity
Implementing ML algos from scratch		 Python scikit-learn PyTorch
Web & DataVis Data visualiztaion of hotels & reviews CSS3 HTML5 JavaScript
Markov Chains Community Detection Python
Pricing Convertible Bonds Python
NLP & Data Analysis Natural disasters in QuoteBank Python Dask Badge
Computer Vision Different optimization methods for ML Python PyTorch

Visited workshops:

Topic Repository Link Technology
Docker workshop LauzHack Docker Workshop Docker
DVC workshop DAG x Visium DVC Workshop DVC Badge

Others, not associated to projects:

PostgreSQL LaTeX C++ Scala

Hilda Abigel Horvath's Projects

epfl-if-case1 icon epfl-if-case1

Codes for the solution to Tottenham Case Study for the Introduction to Finance course.

epfl-ml-project1 icon epfl-ml-project1

In this project, our task was to apply basic machine learning techniques to CERN particle accelerator data to recreate the process of finding Higgs particles. This project was a part of our Machine Learning Course at EPFL in 2021 Fall semester.

liveable-cities icon liveable-cities

An open-source tool for calculating spatial indicators for healthy, sustainable cities worldwide using open or custom data.

ml4science_project icon ml4science_project

Classification of ordinal outcomes for the analysis of injury severity using machine learning methods.

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