https://github.com/revodavid/PracticalAI
AIF01 Practical AI for the Working Software Engineer
https://github.com/revodavid/PracticalAI
Last synced: 4 months ago
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AIF01 Practical AI for the Working Software Engineer
- Host: GitHub
- URL: https://github.com/revodavid/PracticalAI
- Owner: revodavid
- License: mit
- Created: 2018-12-02T20:47:16.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2021-01-05T00:04:14.000Z (over 4 years ago)
- Last Synced: 2024-08-13T07:15:42.540Z (8 months ago)
- Language: Roff
- Size: 39.3 MB
- Stars: 50
- Watchers: 3
- Forks: 19
- Open Issues: 5
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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- jimsghstars - revodavid/PracticalAI - AIF01 Practical AI for the Working Software Engineer (Roff)
README
# Practical AI for the Working Software Engineer
by David M Smith ([`@revodavid`](https://twitter.com/revodavid)), Cloud Advocate at Microsoft
**Last updated**: December 4, 2018
Presented at:
* [AI Live](https://live360events.com/Events/Orlando-2018/Sessions/Friday/AIF01-Workshop-Practical-Artificial-Intelligence-for-the-Working-Software-Engineer.aspx) (AIF01), Orlando, December 7 2018
## About these notebooks
This library includes three notebooks to support the workshop:
1. The AI behind Seeing AI. Use the web-interfaces to Cognitive Services to learn about the AI services behind the "Seeing AI" app
2. Computer Vision API with R. Use an R script to interact with the Computer Vision API and generate captions for random Wikimedia images.
3. Custom Vision with R. An R function to classify an image as a "Hot Dog" or "Not Hot Dog", using the Custom Vision service.
4. MNIST with scikit-learn. Use sckikit-learn to build a digit recognizer for the MNIST data using a regression model.
5. MNIST with tensorflow. Use Tensorflow (from Python) to build a digit recognizer for the MNIST data using a convolutional neural network.
These notebooks are hosted on Azure Notebooks at https://notebooks.azure.com/davidsmi/projects/practicalai, where you can run them interactively. You can also download them to run them using Jupyter.
Find the [slides for the workshop](https://github.com/revodavid/PracticalAI/blob/master/AIF01%20Practical%20AI%20for%20the%20Working%20Software%20Engineer.pdf) here.
## Setup (for use in Azure Notebooks)
* Sign in to Azure Notebooks. You'll need a Microsoft Account: your O365, Xbox, or Hotmail account will work.
If you're new to Notebooks, check out the [Jupyter Notebook documentation](http://jupyter.readthedocs.io/en/latest/index.html) and the [Azure Notebook documentation](https://docs.microsoft.com/en-us/azure/notebooks/?WT.mc_id=AIlive-workshop-davidsmi).
* If you have an iPhone, install the free [SeeingAI app](https://www.microsoft.com/seeing-ai?WT.mc_id=AIlive-workshop-davidsmi).
* (optional) To generate keys and use Azure services, you'll need an Azure subscription. You can get a [free Azure account here](https://azure.microsoft.com/free?WT.mc_id=AIlive-workshop-davidsmi), with $200 in free credits for new subscribers. You'll need a credit card, but most of the things we'll use in this workshop will be free.
## Contact
If you get stuck or just have other questions, you can contact me here:
David Smith `[email protected]`
Twitter: [@revodavid](https://twitter.com/revodavid)