Displaying 1 to 9 from 9 results

alibi-detect - Algorithms for outlier, adversarial and drift detection

  •    Python

Alibi Detect is an open source Python library focused on outlier, adversarial and drift detection. The package aims to cover both online and offline detectors for tabular data, text, images and time series. Both TensorFlow and PyTorch backends are supported for drift detection. For more background on the importance of monitoring outliers and distributions in a production setting, check out this talk from the Challenges in Deploying and Monitoring Machine Learning Systems ICML 2020 workshop, based on the paper Monitoring and explainability of models in production and referencing Alibi Detect.

Sentinl - Kibi + Kibana Alert & Report App for Elasticsearch

  •    Javascript

SENTINL 6 extends Siren Investigate and Kibana with Alerting and Reporting functionality to monitor, notify and report on data series changes using standard queries, programmable validators and a variety of configurable actions - Think of it as a free an independent "Watcher" which also has scheduled "Reporting" capabilities (PNG/PDFs snapshots).

Pyod - A Python Toolkit for Scalable Outlier Detection (Anomaly Detection)

  •    Python

Important Notes: PyOD contains some neural network based models, e.g., AutoEncoders, which are implemented in keras. However, PyOD would NOT install keras and tensorflow automatically. This would reduce the risk of damaging your local installations. You are responsible for installing keras and tensorflow if you want to use neural net based models. An instruction is provided here. Anomaly detection resources, e.g., courses, books, papers and videos.

bell.js - No longer maintained. Use https://github.com/eleme/banshee instead please.

  •    Javascript

Bell.js is a real-time anomalies(outliers) detection system for periodic time series, built to be able to monitor a large quantity of metrics. It collects metrics form statsd, analyzes them with the 3-sigma, once enough anomalies were found in a short time it alerts us via sms/email etc.We eleme use it to monitor our website/rpc interfaces, including api called frequency, api response time(time cost per call) and exceptions count. Our services send these statistics to statsd, statsd aggregates them every 10 seconds and broadcasts the results to its backends including bell, bell analyzes current stats with history data, calculates the trending, and alerts us if the trending behaves anomalous.




skyline - Anomaly detection suite

  •    Python

Skyline is a near real time anomaly detection system, built to enable passive monitoring of hundreds of thousands of metrics, without the need to configure a model/thresholds for each one, as you might do with Nagios. It is designed to be used wherever there are a large quantity of high-resolution time series which need constant monitoring. Once a metrics stream is set up (from StatsD or Graphite or another source), additional metrics are automatically added to Skyline for analysis. Skyline's easily extended algorithms attempt to automatically detect what it means for each metric to be anomalous. The documentation for your version is also viewable in a clone locally in your browser at file://<PATH_TO_YOUR_CLONE>/docs/_build/html/index.html and via the the Skyline Webapp frontend.

anomalize - Tidy anomaly detection

  •    R

anomalize enables a tidy workflow for detecting anomalies in data. The main functions are time_decompose(), anomalize(), and time_recompose(). When combined, it’s quite simple to decompose time series, detect anomalies, and create bands separating the “normal” data from the anomalous data. Load the tidyverse and anomalize packages.

javascript.anomaly - Examples of not obvious behaviors for javascript beginner programmers

  •    

Note that anomaly word has only literary turnover, it's not a technical term.

cora-docs - CoRA Docs

  •    HTML

If you are submitting documentation for the current stable release, submit it to the corresponding branch. For example, documentation for CoRA 1.0 would be submitted to the 1.0 branch. Documentation intended for the next release of CoRA should be submitted to the master branch. If you are new to markdown, fear not...


sigsci-sounds - Listen to the soothing sounds of attacks and anomalies detected by the Signal Sciences web protection platform

  •    Go

Listen to the soothing sounds of attacks and anomalies. The Signal Sciences web protection platform offers a rich API that enables limitless integrations and automation. Or, at least only limited by your imagination. As an example of this, sigsci-sounds is a utility to audibility monitor when Signal Sciences detects attack or anomaly events against your web site. You literally can listen to your site being attacked.






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