Workshops

The following workshops are publicly available.

Xi IoT - Deepomatic Demo Application Guide

Explore a gesture recognition demo application, as seen at .NEXT 2019. Some other gestures have been included, can you find them all?

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Xi IoT - Quick Start for AI Inference

This Xi IoT Quick Start leverages the Xi IoT Trial. The trial is a limited-time, ready-to-deploy implementation of the Xi IoT edge computing platform. The Xi IoT Trial provides pre-built applications and data connectors hosted on its own infrastructure. This instant architecture demonstrates how to quickly develop and test IoT applications in the cloud for seamless deployment to the edge.

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Xi IoT - Facefeed Application Deployment Guide

In this tutorial you’ll deploy an application called “Facefeed” using the Xi IoT SaaS control plane. The application and its data pipelines are deployed to a Xi Edge running in Xi Cloud. This application ingests a video stream using the real time streaming protocol (RTSP), and uses machine learning to detect known faces.

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Xi IoT - Data Pipelines - Getting Started Guide
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PHP API Lab v1.1

Use the Nutanix REST APIs to build a custom dashboard based on Laravel PHP.

Estimated time to complete: 60-90 minutes

Requirements:

- Nutanix Acropolis or Community Edition cluster, with access to Prism Element.
- Mac/Linux/Windows laptop/PC or virtual machine with administrative permissions to install software
- An active internet connection from your laptop/desktop

Optional requirements:

- Access to a Nutanix Frame session, if running this lab in a presenter-run environment

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Python API Lab v1.1

Use the Nutanix REST APis to build a custom dashboard based on Python Flask.

Estimated time to complete: 60-90 minutes

Requirements:

- Nutanix Acropolis or Community Edition cluster, with access to Prism Element.
- Mac/Linux/Windows laptop/PC or virtual machine with administrative permissions to install software
- An active internet connection from your laptop/desktop

Optional requirements:

- Access to a Nutanix Frame session, if running this lab in a presenter-run environment

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