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Search results for machine learning interpretable ai
interpretable-ai
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machine-learning
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21 search results found
Pytorch Grad Cam
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8,723
Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
Interpret
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5,992
Fit interpretable models. Explain blackbox machine learning.
Awesome Machine Learning Interpretability
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3,241
A curated list of awesome responsible machine learning resources.
Awesome Interpretable Machine Learning
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856
Interpretable_machine_learning_with_python
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629
Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.
Mli Resources
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405
H2O.ai Machine Learning Interpretability Resources
Explainx
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375
Explainable AI framework for data scientists. Explain & debug any blackbox machine learning model with a single line of code. We are looking for co-authors to take this project forward. Reach out @
[email protected]
Zennit
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151
Zennit is a high-level framework in Python using PyTorch for explaining/exploring neural networks using attribution methods like LRP.
Xaience
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100
All about explainable AI, algorithmic fairness and more
Deep_xf
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84
Package towards building Explainable Forecasting and Nowcasting Models with State-of-the-art Deep Neural Networks and Dynamic Factor Model on Time Series data sets with single line of code. Also, provides utilify facility for time-series signal similarities matching, and removing noise from timeseries signals.
Machine Learning
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68
Material related to my book Intuitive Machine Learning. Some of this material is also featured in my new book Synthetic Data and Generative AI.
Fat Forensics
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63
Modular Python Toolbox for Fairness, Accountability and Transparency Forensics
Te2rules
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25
Python library to explain Tree Ensemble models (TE) like XGBoost, using a rule list.
Prototorch
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19
ProtoTorch is a PyTorch-based Python toolbox for bleeding-edge research in prototype-based machine learning algorithms.
Interpretable Ml
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17
Techniques & resources for training interpretable ML models, explaining ML models, and debugging ML models.
Whitebox Part1
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16
In this part, i've introduced and experimented with ways to interpret and evaluate models in the field of image. (Pytorch)
Beyond Neural Scaling
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15
Implementation of Beyond Neural Scaling beating power laws for deep models and prototype-based models
Mllp
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12
The code of AAAI 2020 paper "Transparent Classification with Multilayer Logical Perceptrons and Random Binarization".
Hc_ml
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12
Slides, videos and other potentially useful artifacts from various presentations on responsible machine learning.
Article Information 2019
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10
Article for Special Edition of Information: Machine Learning with Python
Jsm_2018_paper
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8
Paper for 2018 Joint Statistical Meetings: https://ww2.amstat.org/meetings/jsm/2018/onlinepro
Prosemble
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6
A python project for prototype-based machine learning models
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