A library for debugging/inspecting machine learning classifiers and explaining their predictions
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Updated
May 1, 2022 - Jupyter Notebook
A library for debugging/inspecting machine learning classifiers and explaining their predictions
My code from the bootcamp.
A Laravel package making a diagram of your models, relations and the ability to build them with it
OmniXAI: A Library for eXplainable AI
Solutions for the collection of TypeScript type challenges with explanations
Pytorch Implementation of recent visual attribution methods for model interpretability
I'm currently preparing for my CCNA 200-301 Exam. During this preparation, I build some labs on various topics of Networking with the help of Cisco Packet Tracer. I hope, these labs will help you too during your preparations. (View README for Explanation).
Code for our USENIX Security 2021 paper -- CADE: Detecting and Explaining Concept Drift Samples for Security Applications
TalkToModel gives anyone with the powers of XAI through natural language conversations 💬!
Code from obscurejavascript.tumblr.com in an easy to download format
Odoo Best Practices - Online Book
A Wiki about common mistakes when using the Arduino Wire library.
Open source library for angular apps to illustrate custom material pages content with steps (ideal for tutorials and explanations purposes)
Generating and validating natural-language explanations.
FULL Implementation of RCNN from scratch
Local explanations with uncertainty 💐!
FeatureTour - Enhance your WPF applications with interactive tutorials!
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