Explainable AI Whiteboard Technical Series: Overview

AI & ML
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.”

Technical Whiteboard Series: AI Overview

Discover how the journey to an AI-Native Network involves rich data, AI primitives, a comprehensive data science toolbox, and a virtual assistant. We delve into various data science tools, from regression to deep learning, and explain their roles in creating a self-driving network.


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You’ll learn

  • The various data science tools and techniques, such as mutual information, decision trees, and reinforcement learning

  • The components required for evolving a network into a self-driving system, including rich data, AI primitives, and a virtual assistant

  • How these AI tools optimize wired and wireless network settings to deliver the best user experience for employees, customers, and guests

Who is this for?

Network Professionals Business Leaders

Resources

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Transcript

0:10 this series explore some of the key

0:12 tools within our Rich data science

0:13 toolbox that powers the AI native

0:16 Enterprise the tools are built into the

0:18 Juniper Mist AI native platform that

0:21 delivers an amazing experience to your

0:23 employees customers and

0:25 guests as you learn more about the AI

0:27 technology used by Juniper mist you'll

0:30 see that the journey to an AI native

0:32 Network requires Rich data AI Primitives

0:35 A well-stocked data science toolbox and

0:37 a virtual

0:39 assistant all of these components are

0:41 required as the network evolves to

0:43 become self-driving the data science

0:45 tools vary in algorithm complexity and

0:48 increasing intelligence from regression

0:50 to deep

0:52 learning Mutual information is used to

0:55 understand the scope of impact of an

0:56 issue decision trees or supervised

0:58 learning used to determine Network

1:00 Health by analyzing data extracting

1:03 feature information and building models

1:05 to predict failure or success of common

1:07 networking problems lstm or long

1:10 short-term memory networks are a special

1:12 kind of recurrent neural network that

1:15 use reasoning and previous Network

1:16 events to make informed decisions on

1:18 current network issues reinforcement

1:21 learning is used to realize a

1:22 self-driving Network that learns and

1:24 optimizes wired and wireless settings

1:27 for the best user experience to learn

1:29 learn more about any of these tools and

1:31 the data science toolbox watch our AI

1:34 technical whiteboard series

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