Practical AI for the Working Software Engineer
by David M Smith (
@revodavid), Cloud Advocate at Microsoft
Last updated: December 4, 2018
- AI Live (AIF01), Orlando, December 7 2018
About these notebooks
This library includes three notebooks to support the workshop:
- The AI behind Seeing AI. Use the web-interfaces to Cognitive Services to learn about the AI services behind the "Seeing AI" app
- Computer Vision API with R. Use an R script to interact with the Computer Vision API and generate captions for random Wikimedia images.
- Custom Vision with R. An R function to classify an image as a "Hot Dog" or "Not Hot Dog", using the Custom Vision service.
- MNIST with scikit-learn. Use sckikit-learn to build a digit recognizer for the MNIST data using a regression model.
- 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 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.
If you get stuck or just have other questions, you can contact me here: