AIF01 Practical AI for the Working Software Engineer
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README.md

Practical AI for the Working Software Engineer

by David M Smith (@revodavid), Cloud Advocate at Microsoft

Last updated: December 4, 2018

Presented at:

  • AI Live (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 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 and the Azure Notebook documentation.

  • If you have an iPhone, install the free SeeingAI app.

  • (optional) To generate keys and use Azure services, you'll need an Azure subscription. You can get a free Azure account here, 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 davidsmi@microsoft.com
Twitter: @revodavid