nuclearglow / machine-learning

machine-learning

• experiments irgebwdwelche Skripte oder so
• blechhuette

Install

conda install -c conda-forge ipdb
conda install -c conda-forge black

project/ structure

data/ * contains the data sources to be worked on models/ * contains models and other exported, loadable data (joblift pkl) pipeline/ * transformers/ - contains pipeline transfomers * pipeline.py - contains all pipelines, uses transformers

/ - the root project contains scripts 01_get_data.py - download / procure data and save to data/ 02_data_visualization.py - scriupts to look at data (spyder) 03_data_preparation.py - prepare data for modeling 04_modeling.py - build models and optimize

Tools

ls alias https://github.com/ogham/exa

.bashrc

Detect which ls flavor is in use

if ls --color > /dev/null 2>&1; then # GNU ls colorflag="--color" export LS_COLORS='no=00:fi=00:di=01;31:ln=01;36:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:ex=01;32:.tar=01;31:.tgz=01;31:.arj=01;31:.taz=01;31:.lzh=01;31:.zip=01;31:.z=01;31:.Z=01;31:.gz=01;31:.bz2=01;31:.deb=01;31:.rpm=01;31:.jar=01;31:.jpg=01;35:.jpeg=01;35:.gif=01;35:.bmp=01;35:.pbm=01;35:.pgm=01;35:.ppm=01;35:.tga=01;35:.xbm=01;35:.xpm=01;35:.tif=01;35:.tiff=01;35:.png=01;35:.mov=01;35:.mpg=01;35:.mpeg=01;35:.avi=01;35:.fli=01;35:.gl=01;35:.dl=01;35:.xcf=01;35:.xwd=01;35:.ogg=01;35:.mp3=01;35:.wav=01;35:' else # macOS ls colorflag="-G" export LSCOLORS='BxBxhxDxfxhxhxhxhxcxcx' fi

alias exa

alias ls='exa' alias ll='exa --all --header --long --group --classify --git'

Python

IPDB Debugger

https://nornir.readthedocs.io/en/latest/howto/ipdb_how_to_inspect_complex_structures.html

Run script in Python Shell

python
>>> exec(open('script.py').read())