Author: Srividya Iyer
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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
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The Art and Science of Network Anomaly Detection – Part 2
In this post, we will look at different network anomaly detection methods, challenges and implementations of anomaly detection.
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The Art and Science of Network Anomaly Detection – Part 1
In this post, we will attempt to define what network anomalies are, identify their causes and classify them using various criteria.
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Network Analytics – How to transition from Reactive to Proactive
In this post, we will look at different types of Network Analytics and how they can be used in network operations.