https://github.com/cloudflightio/azurewithmachinelearning
Guided project for creating a serverless azure function in combination with a machine learning model
https://github.com/cloudflightio/azurewithmachinelearning
Last synced: about 1 month ago
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Guided project for creating a serverless azure function in combination with a machine learning model
- Host: GitHub
- URL: https://github.com/cloudflightio/azurewithmachinelearning
- Owner: cloudflightio
- License: apache-2.0
- Created: 2022-06-14T07:13:47.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2024-11-07T08:47:43.000Z (over 1 year ago)
- Last Synced: 2025-04-26T09:33:21.182Z (10 months ago)
- Language: Python
- Homepage:
- Size: 31.8 MB
- Stars: 1
- Watchers: 2
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Azure with Machine Learning Workshop
Welcome to the Azure with Machine Learning workshop! This repository contains the code and instructions for an
interactive coding session focused on cloud-native development on Azure, serverless functions, and machine learning.
## Project Overview
In this project, you'll create a serverless Azure function that integrates with a machine learning model. The function
will accept an image upload and return information about the image, such as age and emotions.
## Prerequisites
Before you begin, ensure you have the following:
### Find a Team
- This is a Team Exercise. Form Groups of 2-3 students.
### Azure Account
- Each team needs a free Azure account:
- Create Azure Account https://azure.microsoft.com/free/?ref=microsoft.com&utm_source=microsoft.com&utm_medium=docs&utm_campaign=visualstudio
- If eligible, use the Azure for Students offer. https://azure.microsoft.com/en-gb/free/students/
### Tools and Software
#### Automatic Setup
- If you have `nix` installed, use the flake: from project-root run `nix develop`. Everything will be set up for you. You can use the `setup.sh` script to install `nix`.
#### Alternatively
- **Azure CLI**: Install Azure CLI https://learn.microsoft.com/en-us/cli/azure/install-azure-cli
- **Azure Functions Core Tools**: Install Azure Functions Core Tools https://docs.microsoft.com/en-us/azure/azure-functions/functions-run-local?tabs=v4%2Cwindows%2Ccsharp%2Cportal%2Cbash#install-the-azure-functions-core-tools
- **Visual Studio Code**: Download Visual Studio Code https://code.visualstudio.com/
- Install these extensions:
- REST Client https://marketplace.visualstudio.com/items?itemName=humao.rest-client
- Python https://marketplace.visualstudio.com/items?itemName=ms-python.python
- Azure Functions https://marketplace.visualstudio.com/items?itemName=ms-azuretools.vscode-azurefunctions
- **Python 3.11 on PATH**: Download Python 3.11 https://www.python.org/downloads/release/python-3110/
- Install these Python packages:
- `azure-functions`
- `opencv-python`
- `onnxruntime`
- `numpy`
- Set up a virtual environment in the `./HttpTrigger` directory:
```bash
python3.11 -m venv .venv
```
## Getting Started
Follow these steps to set up and run the project:
1. **Login to Azure**
- Open the terminal in Visual Studio Code and run:
```bash
az login
```
- This will open a browser window for you to log in.
2. **Set Up the Project**
- Clone this repository and navigate to the project directory.
- Open the folder starting with `01` in Visual Studio Code.
- Follow the instructions in the subsequent folders (`02`, `03`, etc.).
## Troubleshooting
If you encounter any issues, please reach out to us for assistance. We're here to help you succeed!