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shubhomoydas / ad_examples

Star 755

A collection of anomaly detection methods (iid/point-based, graph and time series) including active learning for anomaly detection/discovery, bayesian rule-mining, description for diversity/explanation/interpretability. Analysis of incorporating label feedback with ensemble and tree-based detectors. Includes adversarial attacks with Graph Convolutional Network.
streaming timeseries time-series lstm generative-adversarial-network gan rnn autoencoder ensemble-learning trees active-learning concept-drift graph-convolutional-networks interpretability anomaly-detection adversarial-attacks explaination anogan unsuperivsed nettack
  • Updated Feb 10, 2022
  • Python

DivyaGodayal / CoderChef-Kitchen

Star 350

The official repository for our programming kitchen which consists of 50+ delicious programming recipes having all the interesting ingredients ranging from dynamic programming, graph theory, linked lists and much more. All the articles contain beautiful images and some gif/video at times to help clear important concepts.
python java algorithm programming linked-list leetcode graph string blogging interview interview-practice interview-questions dynamic-programming trees greedy-algorithms editorial datastructure interview-preparation 100daysofcode codenewbie
  • Updated Aug 7, 2019
  • Python

justindujardin / mathy

Star 89
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Update API doc generation script to run with lint-staged

justindujardin
justindujardin commented Jan 28, 2020

I noticed that I forgot to update the API docs for a refactor that moved mathy.mathy to mathy.api.

Currently, you have to run:

cd libraries/website
sh tools/docs.sh

And it generates all the API doc files. This means it's too slow to run all the time. It should be updated to run as part of lint-staged and support passing individual files on the command-line, similar to th

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enhancement help wanted good first issue

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