Darius Morawiec's Projects
[unmaintained] Reading values of multiple MPU-6050's.
Small collection of my written command line helpers.
Plugin repository for BitBar
Course materials/Homework materials for the FREE MOOC course on "Creative Applications of Deep Learning w/ Tensorflow" #CADL
OS-agnostic, system-level binary package manager and ecosystem
BitBar plugin to list all created conda environments and to open a new session with a chosen environment.
TFDS is a collection of datasets ready to use with TensorFlow, Jax, ...
A Python implementation of Deep Belief Networks with scikit-learn support
Walk up and down in revisions of a Git repository.
The largest collection of useful .gitignore templates
LAVIS - A One-stop Library for Language-Vision Intelligence
Contributed library to use the Leap Motion in Processing.
Generate and update magically a table of contents based on the headlines of a parsed markdown file.
A library of extension and helper modules for Python's data analysis and machine learning libraries.
Initial data evaluation of ModaNet by eBay.
Contributed library to use multiple Myo's in Processing.
[unmaintained] A webcrawler as executable RubyGem, which grabs fine-grained data of your personal Nike+ runs and saves these as XML and JSON files.
Implementation of the $1 Unistroke Recognizer, a two-dimensional template based gesture recognition, in CoffeeScript.
Implementation of the $1 Gesture Recognizer, a two-dimensional template based gesture recognition, for Processing.
Tensorflow Backend and Frontend for ONNX
Use the command line tool `openml` to interact with the official API of OpenML.
It's an interactive tool for developers to test defined specifiers for version handling.
Python dependency management and packaging made easy.
A Python wrapper for Google Tesseract
Implementation of the Rapid Automatic Keyword Extraction algorithm in Ruby, a multi-word keywords extraction.
[unmaintained] Wrapper to use Redis in Processing. It's based on Jedis, a small Java client by Jonathan Leibiusky.
Make the Redis Mass Insertion by using the REdis Serialization Protocol (RESP) simple.
generate release PRs based on the conventionalcommits.org spec
scikit-learn: machine learning in Python