There are 2 repositories under explanation topic.
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 💬!
Learn how URLs work by visually inspecting their structure.
Code from obscurejavascript.tumblr.com in an easy to download format
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)
Local explanations with uncertainty 💐!
FeatureTour - Enhance your WPF applications with interactive tutorials!
Playground and evolution of learnings done in react native with typescript
Explain a black-box module in natural language.
For <Does It Make Sense? And Why? A Pilot Study for Sense Making and Explanation>. Accepted by ACL2019
All Design Patterns code and explanation will be here, explanation will be inside each folder of specific Design Pattern and the code will be written in C# at environment Visual Studio Code.
A time series forecasting project from Kaggle that uses Seq2Seq + LSTM technique to forecast the headcounts. Detailed explanation on how the special neural network structure works is provided.
Notes from web development bootcamp courses on Udemy by Colt Steele
JS application from scratch without any dependencies
Local Interpretable Model-Agnostic Explanations For Time Series Forecast Models
A marching squares implementation in JS and an explanation website to go along with it
This repository will be really helpful, if you want to learn from the scratch in Python Programming Languages. Also, makes your strong in Basic Python.
explainy is a Python library for generating machine learning model explanations for humans
😃 내가 보려고 만든 안드로이드 면접 질문 대비 자료
Helpful examples for understanding spark