Topic: machine-learning-interpretability Goto Github
Some thing interesting about machine-learning-interpretability
Some thing interesting about machine-learning-interpretability
machine-learning-interpretability,The code of AAAI 2020 paper "Transparent Classification with Multilayer Logical Perceptrons and Random Binarization".
User: 12wang3
machine-learning-interpretability,Overview of machine learning interpretation techniques and their implementations
User: akifcinar
machine-learning-interpretability,Predicting the Likelihood to Purchase a Financial Product Following a Direct Marketing Campaign
User: diegousaiuk
Home Page: https://diegousai.io/
machine-learning-interpretability,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]
Organization: explainx
Home Page: https://www.explainx.ai
machine-learning-interpretability,Article for Special Edition of Information: Machine Learning with Python
Organization: h2oai
Home Page: https://www.mdpi.com/journal/information/special_issues/ML_Python
machine-learning-interpretability,H2O.ai Machine Learning Interpretability Resources
Organization: h2oai
machine-learning-interpretability,Rule Extraction from Bayesian Networks
User: hayesall
Home Page: https://hayesall.com/blog/bayes-net-rule-extraction/
machine-learning-interpretability,A curated list of awesome responsible machine learning resources.
User: jphall663
machine-learning-interpretability,Sample use case for Xavier AI in Healthcare conference: https://www.xavierhealth.org/ai-summit-day2/
User: jphall663
machine-learning-interpretability,Slides, videos and other potentially useful artifacts from various presentations on responsible machine learning.
User: jphall663
machine-learning-interpretability,Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.
User: jphall663
machine-learning-interpretability,Paper for 2018 Joint Statistical Meetings: https://ww2.amstat.org/meetings/jsm/2018/onlineprogram/AbstractDetails.cfm?abstractid=329539
User: jphall663
machine-learning-interpretability,Fairness in AI and Machine Learning
User: navdeep-g
machine-learning-interpretability,Techniques & resources for training interpretable ML models, explaining ML models, and debugging ML models.
User: navdeep-g
machine-learning-interpretability,This project contains the data, code and results used in the paper title "On the relationship of novelty and value in digitalization patents: A machine learning approach".
User: nilsdenter
machine-learning-interpretability,TeleGam: Combining Visualization and Verbalization for Interpretable Machine Learning
Organization: poloclub
Home Page: https://poloclub.github.io/telegam/
machine-learning-interpretability,An interpretable machine learning pipeline over knowledge graphs
Organization: sdm-tib
machine-learning-interpretability,Demonstration of InterpretME, an interpretable machine learning pipeline
Organization: sdm-tib
Home Page: https://github.com/SDM-TIB/InterpretME
machine-learning-interpretability,Default Risk Prediction from bank dataset with Interpretable Machine Learning
User: tommykangdra
machine-learning-interpretability,INVASE: Instance-wise Variable Selection . For more details, read the paper "INVASE: Instance-wise Variable Selection using Neural Networks," International Conference on Learning Representations (ICLR), 2019.
Organization: vanderschaarlab
machine-learning-interpretability,XMLX GitHub configuration
Organization: xmlx-io
Home Page: https://github.com/xmlx-io
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