Last Sunday, I took a beginner’s session on getting started with artificial intelligence as part of AI-Creatives meetup Code & Coffee. To get the fancy of attendees, I picked up computer vision; more specifically, image recognition using deep learning.
As time was deliberately limited (90 mins), I focused on inference more than training. Deep learning, as you know, requires time (weeks to months) and resources (specialized GPUs). I based my demo on the Tensorflow’s image retraining tutorial.
The core idea was to quickly retrain a trained ImageNet model, and then create an API around it for inferences. This API would then be tested by using it on a webpage. I think the session went well. You can see the deck I used here. Source code for classifier, API and webpage is on GitHub.