Whiteboard Technical Series: Artificial Intelligence Overview

A computer-generated whiteboard image showing three boxes. Box one shows zeros and ones, with a caption stating, “Rich Data.” Box two shows Bluetooth and WiFi icons, with captions stating, “AI Primitives.” Box three shows a cube surrounded by swirling atomic electrons with a caption that states, “Data Science Toolbox.”

A beginner’s guide to Juniper’s Data Science toolbox

In the first video of our AI technical series, discover some of the key tools within Juniper’s rich Data Science toolbox and see how they power the Juniper AI-driven Enterprise.

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You’ll learn

  • The various elements that a journey to an AI-driven network requires 

  • How the Data Science tools vary in algorithm complexity and increasing intelligence

  • How Juniper uses the following tools in our AI platform: Mutual Information, Decision Trees, Reinforcement Learning, and LSTM RNN

Who is this for?

Network Professionals Business Leaders



00:07 this series explores some of the key

00:09 tools within our rich data science

00:11 toolbox that powers the AI driven

00:13 enterprise the tools are built into the

00:16 Juniper mist AI driven platform that

00:19 delivers an amazing experience to your

00:21 employees customers and guests as you

00:25 learn more about the AI technology used

00:27 by Juniper Mist you'll see that the

00:29 journey to an AI driven network requires

00:31 rich data AI primitives a well stocked

00:34 data science toolbox and a virtual

00:37 assistant all of these components are

00:39 required is the network evolves to

00:41 become self-driving the data science

00:44 tools vary in algorithm complexity and

00:47 increasing intelligence from regression

00:48 to deep learning mutual information is

00:52 used to understand the scope of impact

00:54 of an issue decision trees are

00:56 supervised learning used to determine

00:58 Network help by analyzing data

01:00 extracting feature information and

01:02 building models to predict failure or

01:04 success of common networking problems

01:08 LST m or long short term memory networks

01:12 are a special kind of a commoner Anette

01:15 work that use reasoning and previous

01:17 network events to make informed

01:19 decisions on current network issues

01:21 reinforcement learning is used to

01:23 realize a self driving network that

01:25 learns and optimizes wired and wireless

01:27 settings for the best user experience to

01:31 learn more about any of these tools and

01:33 the data science toolbox watch our AI

01:35 technical whiteboard series

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