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explainable-ai
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orihime-kitajima
commented
Jul 3, 2019
How to use Watcher / WatcherClient over tcp/ip network?
Watcher seems to ZMQ server, and WatcherClient is ZMQ Client, but there is no API/Interface to config server IP address.
Do I need to implement a class that inherits from WatcherClient?
Machine Learning in one line of code
machine-learning
tensorflow
ml
pytorch
artificial-intelligence
ludwig
automl
explainable-ai
explainable-ml
xai
xai-library
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Updated
Aug 20, 2020 - Python
data-science
machine-learning
interpretable-ai
interpretable-ml
explainable-ai
xai
interpretable-machine-learning
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Updated
Jul 9, 2020 - Python
moDel Agnostic Language for Exploration and eXplanation
black-box
data-science
machine-learning
predictive-modeling
interpretability
explainable-artificial-intelligence
explanations
explainable-ai
explainable-ml
xai
model-visualization
interpretable-machine-learning
iml
dalex
explanatory-model-analysis
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Updated
Aug 18, 2020 - Python
Interpretability and explainability of data and machine learning models
machine-learning
deep-learning
artificial-intelligence
ibm-research
explainable-ai
explainable-ml
xai
ibm-research-ai
codait
trusted-ai
trusted-ml
explainabil
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Updated
Aug 17, 2020 - Python
Code, exercises and tutorials of my personal blog ! 📝
python
machine-learning
statistics
dataviz
ai
deep-learning
tensorflow
example
keras
tutorials
pytorch
explainable-ai
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Updated
Feb 18, 2020 - Jupyter Notebook
XAI - An eXplainability toolbox for machine learning
machine-learning
ai
evaluation
ml
artificial-intelligence
upsampling
bias
interpretability
feature-importance
explainable-ai
explainable-ml
xai
imbalance
downsampling
explainability
bias-evaluation
machine-learning-explainability
xai-library
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Updated
Oct 5, 2019 - Python
Generate Diverse Counterfactual Explanations for any machine learning model.
machine-learning
deep-learning
explainable-ai
explainable-ml
xai
interpretable-machine-learning
counterfactual-explanations
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Updated
Aug 18, 2020 - Python
Leave One Feature Out Importance
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Updated
Jul 2, 2020 - Python
machine-learning
computer-vision
deep-learning
neural-network
explainable-ai
interpretable-machine-learning
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Updated
Mar 29, 2019 - Jupyter Notebook
machine-learning
predictive-modeling
interactive-visualizations
interpretability
explainable-artificial-intelligence
explainable-ai
explainable-ml
xai
model-visualization
interpretable-machine-learning
iml
explainability
explanatory-model-analysis
explainable-machine-learning
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Updated
Aug 17, 2020 - R
A repository for explaining feature attributions and feature interactions in deep neural networks.
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Updated
May 1, 2020 - Jupyter Notebook
Using / reproducing ACD (ICLR 2019) from the paper "Hierarchical interpretations for neural network predictions"
python
data-science
machine-learning
statistics
deep-neural-networks
ai
deep-learning
neural-network
jupyter-notebook
ml
pytorch
artificial-intelligence
convolutional-neural-networks
acd
interpretation
interpretability
feature-importance
explainable-ai
iclr2019
explainability
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Updated
Jul 23, 2020 - Jupyter Notebook
Pytorch implementation of "Explainable and Explicit Visual Reasoning over Scene Graphs "
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Updated
Mar 17, 2019 - Python
machine-learning
deep-learning
sentiment-analysis
tensorflow
transformers
interpretability
aspect-based-sentiment-analysis
explainable-ai
explainable-ml
distill
bert-embeddings
transformer-models
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Updated
Aug 19, 2020 - Python
Causal Explanation (CXPlain) is a method for explaining the predictions of any machine-learning model.
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Updated
Jan 27, 2020 - Python
Code for using CDEP from the paper "Interpretations are useful: penalizing explanations to align neural networks with prior knowledge" https://arxiv.org/abs/1909.13584
python
data-science
machine-learning
ai
deep-learning
neural-network
jupyter-notebook
ml
pytorch
artificial-intelligence
convolutional-neural-network
fairness
interpretability
cdep
feature-importance
recurrent-neural-network
interpretable-deep-learning
explainable-ai
explainability
fairness-ml
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Updated
Jul 23, 2020 - Jupyter Notebook
ExplainX is a fast, light-weight, and scalable explainable AI framework for data scientists to explain and debug any black-box model.
python
machine-learning
ai
artificial-intelligence
trust
transparency
blackbox
bias
interpretability
explainable-artificial-intelligence
interpretable-ai
explainable-ai
xai
interpretable-machine-learning
explainx
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Updated
Aug 19, 2020 - Jupyter Notebook
A fast Tsetlin Machine implementation employing bit-wise operators, with MNIST demo.
machine-learning
artificial-intelligence
mnist
pattern-recognition
bitwise-operators
frequent-pattern-mining
rule-based
explainable-ai
tsetlin-machine
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Updated
Aug 16, 2019 - C
[CVPR 2020 Oral] Interpretable and Accurate Fine-grained Recognition via Region Grouping
pytorch
interpretability
celeba-dataset
fine-grained-classification
explainable-ai
face-segmentation
pytorch-implementation
part-based-models
cvpr2020
cvpr-2020
cvpr-oral
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Updated
Jul 8, 2020 - Python
Detect model's attention
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Updated
Jul 2, 2020 - Jupyter Notebook
Explaining the output of machine learning models with more accurately estimated Shapley values
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Updated
Aug 18, 2020 - R
Workshop: Explanation and exploration of machine learning models with R and DALEX at eRum 2020
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Updated
Jun 20, 2020 - R
FairPut - Machine Learning Fairness Framework with LightGBM — Explainability, Robustness, Fairness (by @firmai)
contrastive
counterfactual
explainable-ai
explainable-ml
xai
interpretable-machine-learning
fairness-ai
aif360
fairness-ml
alibi
prototypical
aix360
fairness-indicators
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Updated
Jun 5, 2020 - Jupyter Notebook
reinforcement-learning
tensorflow
relational-networks
proximal-policy-optimization
ppo
explainable-ai
self-attention
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Updated
Apr 15, 2019 - Python
code release for Representer point Selection for Explaining Deep Neural Network in NeurIPS 2018
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Updated
Feb 7, 2019 - Jupyter Notebook
Fast approximate Shapley values in R
variable-importance
explainable-ai
explainable-ml
xai
shapley
interpretable-machine-learning
shapley-values
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Updated
Feb 2, 2020 - R
Examples of Data Science projects and Artificial Intelligence problems
python
data-science
machine-learning
natural-language-processing
reinforcement-learning
computer-vision
deep-learning
time-series
examples
regression
data-visualization
artificial-intelligence
classification
explainable-ai
explainable-ml
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Updated
Aug 4, 2020 - Jupyter Notebook
In the wild extraction of entities that are found using Flair and displayed using a very elegant front-end.
visualization
python
nlp
flask
deployment
angular4
ner
nlp-machine-learning
flair
entity-extraction
explainable-ai
flair-embeddings
contextual-embeddings
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Jul 31, 2020 - HTML
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