Pinned Repositories
Algorithmic_Fairness_COMPAS
This is a project I have done for the module IM903 (Warwick University). I am exploring algorithmic fairness on the examples of the COMPAS algorithm.
Applied_Dynamical_Systems_MA998
This work was done as part of the module Applied Dynamical Systems (MA998). It contains some basic analysis of dynamical systems (numerical analysis of the Atri model for intercellular calcium dynamics, one- and two-dimensional maps, Lyapunov exponents.. )
Computational_Biology_Basics_in_Julia
In this notebook basic methods of computational biology are implemented in Julia (Needleman-Wunsch Algorithm, Neighbour-Joining Algorithm, Suffix trees, Phylogenetic trees, ClustalW Algorithm, tSNE visualisations). This was done as part of the module Computational Biology (CS903, Warwick University) [Julia]
Data_Analysis_Examples_in_Julia
This repository contains some basic examples of data analysis done in Julia (Spotting fake data and Benfords Law, One-sided and two-sided test differences, Posterior for a normal distribution, Analysis of Exoplanet data, Simulation of an autoregressive model). This work was done as part of the module Data Analysis (Warwick University, MA930, Masters Level). [Julia]
Digital_Pathology_CellDensityEstimation
This work is part of the course CS904 (Computational Biology, Warwick University). Different methods for separating tissue from background in a slide that was stained with hematoxylin and eosin are explored. Further work includes the application of cell density measures. [MachineLearning]
Digital_Pathology_DeepLearningVSClassicalFeatures_PYTHON_MATLAB
This work is part of the course CS904 (Computational Biology, Warwick University). We classify tissues slides into eight different classes with a deep learning approach and compare the results to classification with a SVM that was trained on handcrafted features.
Numerical-Methods_in_Julia
These workbooks are part of the assignments for Numerical Methods (MA934, Masters Level). All code is written in Julia. [Julia]
prompt_generator
social_agent_based_modelling
Julia-Machine-Learning-Review
annika-stechemesser's Repositories
annika-stechemesser/Digital_Pathology_DeepLearningVSClassicalFeatures_PYTHON_MATLAB
This work is part of the course CS904 (Computational Biology, Warwick University). We classify tissues slides into eight different classes with a deep learning approach and compare the results to classification with a SVM that was trained on handcrafted features.
annika-stechemesser/Numerical-Methods_in_Julia
These workbooks are part of the assignments for Numerical Methods (MA934, Masters Level). All code is written in Julia. [Julia]
annika-stechemesser/Algorithmic_Fairness_COMPAS
This is a project I have done for the module IM903 (Warwick University). I am exploring algorithmic fairness on the examples of the COMPAS algorithm.
annika-stechemesser/Applied_Dynamical_Systems_MA998
This work was done as part of the module Applied Dynamical Systems (MA998). It contains some basic analysis of dynamical systems (numerical analysis of the Atri model for intercellular calcium dynamics, one- and two-dimensional maps, Lyapunov exponents.. )
annika-stechemesser/Computational_Biology_Basics_in_Julia
In this notebook basic methods of computational biology are implemented in Julia (Needleman-Wunsch Algorithm, Neighbour-Joining Algorithm, Suffix trees, Phylogenetic trees, ClustalW Algorithm, tSNE visualisations). This was done as part of the module Computational Biology (CS903, Warwick University) [Julia]
annika-stechemesser/Data_Analysis_Examples_in_Julia
This repository contains some basic examples of data analysis done in Julia (Spotting fake data and Benfords Law, One-sided and two-sided test differences, Posterior for a normal distribution, Analysis of Exoplanet data, Simulation of an autoregressive model). This work was done as part of the module Data Analysis (Warwick University, MA930, Masters Level). [Julia]
annika-stechemesser/Digital_Pathology_CellDensityEstimation
This work is part of the course CS904 (Computational Biology, Warwick University). Different methods for separating tissue from background in a slide that was stained with hematoxylin and eosin are explored. Further work includes the application of cell density measures. [MachineLearning]
annika-stechemesser/prompt_generator
annika-stechemesser/social_agent_based_modelling
annika-stechemesser/twint
An advanced Twitter scraping & OSINT tool written in Python that doesn't use Twitter's API, allowing you to scrape a user's followers, following, Tweets and more while evading most API limitations.
annika-stechemesser/twitter_scrape
website hosting my twitter app