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awesome-machine-learning-interpretability
A curated list of awesome responsible machine learning resources.interpretable_machine_learning_with_python
Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.GWU_data_mining
Materials for GWU DNSC 6279 and DNSC 6290.secure_ML_ideas
Practical ideas on securing machine learning modelsGWU_rml
xai_misconceptions
Preprint/draft article/blog on some explainable machine learning misconceptions. WIP!diabetes_use_case
Sample use case for Xavier AI in Healthcare conference: https://www.xavierhealth.org/ai-summit-day2/hc_ml
Slides, videos and other potentially useful artifacts from various presentations on responsible machine learning.responsible_xai
Guidelines for the responsible use of explainable AI and machine learning.jsm_2018_slides
Slides for 2018 Joint Statistical Meetings: https://ww2.amstat.org/meetings/jsm/2018/onlineprogram/AbstractDetails.cfm?abstractid=329539jsm_2018_paper
Paper for 2018 Joint Statistical Meetings: https://ww2.amstat.org/meetings/jsm/2018/onlineprogram/AbstractDetails.cfm?abstractid=329539corr_graph
Short example for creating a correlation graph with Pandas and Gephi.h2oworld_sf_2019
Human-Centered ML Presentation for H2O World SF 2019.ds_interview_qs
Some Data Science Interview Questions (by Me and Former Colleagues at SAS)jsm_2019
Slides for JSM 2019 preso on model debugging strategiesnafsa_2018_slides
Slides for presentation at NAFSA retreatlime_xgboost
Simple package for creating LIMEs for XGBoostds_quick_refs
An Aggregation of a Few Decent Data Science Quick referencesbasic_data_viz_rules_and_links
Some Basic (Hopefully Not Terrible) Data Visualization Rules and Linkspy_chunks
Example code and materials to a chunk and process a file using Python mulitprocessing.keep_the_science_in_data_science
Essay about science and data "science".GWU_DNSC_6301_project
Example project for DNSC 6301bellarmine_py_intro
Code and materials for Python intro. course.automl_resources
A running list of links for AutoML - very unofficial and incompleter_gbm_samples
Some Basic Samples of Using R and H2O to Train Gradient Boosting Machinesxgb_random_grid_search_example
Example code and data for XGBoost random grid search.frank_not_frank
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