• Stars
    star
    11
  • Rank 1,694,829 (Top 34 %)
  • Language
    TeX
  • Created over 6 years ago
  • Updated about 6 years ago

Reviews

There are no reviews yet. Be the first to send feedback to the community and the maintainers!

Repository Details

Slides for 2018 Joint Statistical Meetings: https://ww2.amstat.org/meetings/jsm/2018/onlineprogram/AbstractDetails.cfm?abstractid=329539

More Repositories

1

awesome-machine-learning-interpretability

A curated list of awesome responsible machine learning resources.
3,585
star
2

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.
Jupyter Notebook
669
star
3

GWU_data_mining

Materials for GWU DNSC 6279 and DNSC 6290.
Jupyter Notebook
236
star
4

secure_ML_ideas

Practical ideas on securing machine learning models
TeX
35
star
5

GWU_rml

Jupyter Notebook
34
star
6

xai_misconceptions

Preprint/draft article/blog on some explainable machine learning misconceptions. WIP!
Jupyter Notebook
28
star
7

diabetes_use_case

Sample use case for Xavier AI in Healthcare conference: https://www.xavierhealth.org/ai-summit-day2/
Jupyter Notebook
25
star
8

hc_ml

Slides, videos and other potentially useful artifacts from various presentations on responsible machine learning.
TeX
22
star
9

kdd_2019

Paper and talk from KDD 2019 XAI Workshop
TeX
20
star
10

responsible_xai

Guidelines for the responsible use of explainable AI and machine learning.
Jupyter Notebook
17
star
11

jsm_2018_paper

Paper for 2018 Joint Statistical Meetings: https://ww2.amstat.org/meetings/jsm/2018/onlineprogram/AbstractDetails.cfm?abstractid=329539
TeX
10
star
12

corr_graph

Short example for creating a correlation graph with Pandas and Gephi.
Jupyter Notebook
9
star
13

h2oworld_sf_2019

Human-Centered ML Presentation for H2O World SF 2019.
TeX
9
star
14

ds_interview_qs

Some Data Science Interview Questions (by Me and Former Colleagues at SAS)
6
star
15

jsm_2019

Slides for JSM 2019 preso on model debugging strategies
TeX
5
star
16

nafsa_2018_slides

Slides for presentation at NAFSA retreat
TeX
5
star
17

lime_xgboost

Simple package for creating LIMEs for XGBoost
Jupyter Notebook
5
star
18

ds_quick_refs

An Aggregation of a Few Decent Data Science Quick references
5
star
19

basic_data_viz_rules_and_links

Some Basic (Hopefully Not Terrible) Data Visualization Rules and Links
5
star
20

py_chunks

Example code and materials to a chunk and process a file using Python mulitprocessing.
Python
4
star
21

keep_the_science_in_data_science

Essay about science and data "science".
4
star
22

GWU_DNSC_6301_project

Example project for DNSC 6301
Jupyter Notebook
3
star
23

bellarmine_py_intro

Code and materials for Python intro. course.
Python
3
star
24

automl_resources

A running list of links for AutoML - very unofficial and incomplete
3
star
25

r_gbm_samples

Some Basic Samples of Using R and H2O to Train Gradient Boosting Machines
R
1
star
26

xgb_random_grid_search_example

Example code and data for XGBoost random grid search.
Jupyter Notebook
1
star
27

frank_not_frank

Original, free sample images.
Python
1
star