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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.

awesome-aiops icon awesome-aiops

AIOps学习资料汇总，欢迎一起补全这个仓库，欢迎star

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A curated list of Site Reliability and Production Engineering resources.

deeplearning-500-questions icon deeplearning-500-questions

深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为18个章节，50余万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作，联系[email protected] 版权所有，违权必究 Tan 2018.06

mscred icon mscred

Concise, modular implementation of Multi-Scale Convolutional Recurrent Encoder Decoder: https://arxiv.org/abs/1811.08055

python4datascience.ch icon python4datascience.ch

从0开始接触Python处理数据科学问题。包含Python0基础入门、科学计算工具入门、数学与计算机基础入门、统计学习入门。

pythonfromdatods icon pythonfromdatods

图书《Python编程：从数据分析到数据科学》的配套资源

rrcf icon rrcf

🌲 Implementation of the Robust Random Cut Forest algorithm for anomaly detection on streams

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