This is a collection of code containing concepts and approaches to analysise data in diverse ways. The goal is to represent my expertise in data sience and support my CV with showcasing the experience I list. I hope you enjoy to skim through section that catch the glimpse of your eye!
Quick and dirty analysis of data finding simple relationships, distributions or missing values in data
Covers the following approaches to analyse pattern and relationships in data:
- Hypothesis-Testing: Includes Analysis of Variance (ANOVA), Analysis of Covariance (ANCOVA) and Chi-Squared Testing
- Probaility and Likelihood: Explore scripts that deal with various probability distributions commonly used in statistical analysis, as well as the self implemented MLE approach to fit parameters.
- Regression Model: Discover scripts performing regression analysis to model relationships between variables with linear and multiple regression, GLMS or LMMs and optimzinhg anaylsis with model selection
- Time Series: A script analysing components and stationarity of time series data of air travel.
- Uncertainty Analysis: Learn about how to handle uncertainty in fitting or error propagation.
Represents my experience in analysing data with ML by:
- Supervised Learning: Discover scripts using Deep Learning and other classification approaches like KNN, SVM or BDT.
- Unsupervised Learning In development...
I'm currently documenting further analyses for the directory Machine Learning.