Difference between revisions of "Development"

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* [http://www.splunk.com/en_us/it-operations/artificial-intelligence-aiops.html AIOps: Artificial Intelligence for IT Operations, Modernize and transform IT Operations with solutions built on the only Data-to-Everything platform | splunk>]
 
* [http://www.splunk.com/en_us/it-operations/artificial-intelligence-aiops.html AIOps: Artificial Intelligence for IT Operations, Modernize and transform IT Operations with solutions built on the only Data-to-Everything platform | splunk>]
 
* [http://www.gartner.com/smarterwithgartner/how-to-get-started-with-aiops/ How to Get Started With AIOps | Susan Moore - Gartner]
 
* [http://www.gartner.com/smarterwithgartner/how-to-get-started-with-aiops/ How to Get Started With AIOps | Susan Moore - Gartner]
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Revision as of 14:36, 13 November 2019

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Major differences:

  1. More emphasis on information pipeline management; data collection, preparation, feature determination, and pipeline configuration management.
  2. Developing a machine learning application is more iterative and explorative process than traditional software engineering. Learning / Testing / Validation of models is an upfront task


machine_learning_flow--4j88rajonr_s600x0_q80_noupscale.png

Developing a machine learning application is even more iterative and explorative process than software engineering. Machine learning is applied on problems that are too complicated for humans to figure out (that is why we ask a computer to find a solution for us!). Differences between machine learning and software engineering | Antti Ajanki - Futurice


Agile

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AIOps

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