Category: Machine Learning
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How to implement AI/ML in Networking – 5 Key Considerations
AI/ML holds tremendous potential in making network operations more efficient. However, very few AI/ML implementations actually make it to production environments. The most common reasons for failed implementations are lack of clarity in problem definition, building or buying a solution that is ill suited for the problem at hand and not getting the team on…
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Evolution of Network Baselines – From Statistics to Machine Learning
In this blogpost, we talk about the benefits of having accurate baselines, metrics used, systematic approach to baselining the network and how complex networks can use Machine Learning to create dynamic baselines.
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Feature Engineering at the intersection of Network Data and Machine Learning
In this post, we will talk about different features extracted from network data, tasks and techniques of feature engineering, and why feature engineering is essential to the accuracy of the Machine Learning model.
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It starts with the right data – Categorizing Network Data for Machine Learning
In this post, we will provide a high-level categorization of network data. This data can be used to build a Network Analytics solution using Machine Learning