Name: Philipp Baumann
Type: User
Company: Public Transport
Bio: Working in public transport. In my spare time: developing tools for computational reproducibility. Chemical diagnostics with spectroscopy and data analytics.
Twitter: PhilippBauman15
Location: Bern, Switzerland
Blog: https://spectral-cockpit.com
Philipp Baumann's Projects
Description and usage tutorial for the AWS Public Dataset produced by AfSIS (arn:aws:s3:::afsis)
Inductive transfer learning using the AfSIS spectral library
Ansible is a radically simple IT automation platform that makes your applications and systems easier to deploy. Avoid writing scripts or custom code to deploy and update your applications β automate in a language that approaches plain English, using SSH, with no agents to install on remote systems. https://docs.ansible.com/ansible/
Are you bamboozled by Booleans? Let Bamboolean interpret them.
Black-Box Optimization Toolkit for mlr3
π¨πSearch and Download Data from the Swiss Federal Statistical Office
The blockCV package creates spatially or environmentally separated training and testing folds for cross-validation to provide a robust error estimation in spatially structured environments.
Python package for reading Bruker OPUS files.
Open spectral libraries for home server deployment
Cubist repeated nested group k-fold cross-validation routines (doFuture and doParallel)
R functions for the chemometric analysis of spectra
Source directory to test GitHub action to copy file
Target directory to test GitHub action to copy file to
Simple app for exploring FTIR Spectrum
Convert Color Values into Color Names
Testing copc-rs
fast.ai Courses
The Python programming language
Scientific workflow engine designed for simplicity & scalability. Trivially transition between one off use cases to massive scale production environments
An R package for fitting Quinlan's Cubist regression model
Tricks to get the linux feel β i.e. for mastering Windows lab computers
An open source book to learn data science, data analysis and machine learning, suitable for all ages!
pygeoapi is an OGC Reference Implementation supporting numerous OGC API specifications. This workshop will cover publishing geospatial data to the Web using pygeoapi in support of the suite of OGC API standards.
rstudio::conf(2020) deep learning workshop
Relational data models
dotfiles that reside at `$HOME`s [:penguin: eats :apple:, but we don't eat fish]
An R-focused pipeline toolkit for reproducibility and high-performance computing