Michał Kuźba's repositories
trypophobia-detection
Detecting trypophobic patterns with neural networks
ceterisParibus
Ceteris Paribus Plots (What-If plots) for explanations of a single observation
ceterisParibusExt
Experimental Extensions for Ceteris Paribus Package
chatbot-explainer-titanic
Dialogflow chatbot explaining your chance of survival on Titanic
cleora
Cleora AI is a general-purpose model for efficient, scalable learning of stable and inductive entity embeddings for heterogeneous relational data.
elections-django
Django application for presidential elections 2000 in Poland.
InterpretableMachineLearning2018S
Lecture notes for 'Interpretable Machine Learning' at WUW and UW. Summer semester 2018/2019
kmichael08.github.io
Titanic chatbot - web integration
machine-learning-course
Machine learning assignments
MI2
About MI2 repository http://mi2.mini.pw.edu.pl/
pyCeterisParibus
Python library for Ceteris Paribus Plots
pyss3
A Python package implementing a new interpretable machine learning model for text classification (with visualization tools for Explainable AI :octocat:)
research-activity
Articles, presentations and posters
survxai
Explanations for survival models
taaskly
A Workplace application demonstrating account linking, file preview and composer integration. This models a simple document store with very simple privacy rules.
veridical-flow
Making it easier to build stable, trustworthy data-science pipelines.