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Anomaly Detection Algorithms and Techniques for Real-World Detection Systems
--client
big_apple_py
--show
pygotham_2016
--room Room_CR5 11111 --force
Next: 11 Sensely: Office Automation with the Internet of Things and Python
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Marks
Author(s):
Manojit Nandi
Location
Room CR5
Date
jul Sun 17
Days Raw Files
Start
09:00
First Raw Start
09:13
Duration
00:55:00
Offset
0:13:55
End
09:55
Last Raw End
10:16
Chapters
00:00
0:28:50
Total cuts_time
34 min.
https://2016.pygotham.org/talks/273/anomaly-detection-algorithms-and-techniques-for-real-world-detection-systems
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Finding outliers in a dataset is a challenging problem in which traditional analytical methods often perform poorly. As a result, researchers have developed special algorithms for detecting anomalies. In this talk, I will take about three different families of anomaly detection algorithms: Density-based methods, data streaming methods, and time series methods. I will cover both the mathematical and statistical theory behind these algorithms and provide code implementations. Afterwards, I will discuss useful tips I have learned while implementing threat detection systems in practice.
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2016-07-17/09_13_55.ts
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