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Curation of Non-Mainstream ML Libraries
A curated list of 100+ non-mainstream libraries for all parts of the Machine Learning workflow
library machine-learning data-collection data-augmentation
GANSpace: Discovering Interpretable GAN Controls
This paper describes a simple technique to analyze Generative Adversarial Networks (GANs) and create interpretable controls for image synthesis.
generative-adversarial-networks image-generation interpretability interpretable-gans
CNN Explainer
CNN Explainer uses TensorFlow.js, an in-browser GPU-accelerated deep learning library to load the pretrained model for visualization.
convolutional-neural-networks tensorflow-js interactive interpretability
Interpretable Machine Learning
Extracting human understandable insights from any Machine Learning model.
interpretability ermutation-importance partial-dependence-plots shap-values
AllenNLP Interpret
A Framework for Explaining Predictions of NLP Models
interpretability explainability natural-language-processing api
How to Know When Machine Learning Does Not Now
It is becoming increasingly important to understand how a prediction made by a Machine Learning model is informed by its training data.
adversarial-learning interpretability uncertainty adversarial-examples
Face Mask Detector
A simple Streamlit frontend for face mask detection in images using a pre-trained Keras CNN model + OpenCV and model interpretability.
object-detection streamlit opencv keras
GNNExplainer: Generating Explanations for Graph Neural Networks
General tool for explaining predictions made by graph neural networks (GNNs).
graph-neural-networks interpretability explainability graphs
Explainable Deep Learning: A Field Guide for the Uninitiated
A field guide to deep learning explainability for those uninitiated in the field.
interpretability explainability deep-learning survey
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