Abstract: 

The Machine Learning Canvas is a template for developing intelligent systems based on data and machine learning. It is a visual chart with elements that describe the key aspects of such systems: value proposition, data to learn from, usage of predictions, requirements and measures of performance. It assists teams of scientists, engineers and managers in aligning their activities.

This tutorial will help you get into the right mindset to go beyond the hype around ML and to clearly see how it can have an actual impact in your domain. I’ll present the general structure of the Canvas, how to fill it in, and some examples of the Canvas in action.

Bio: 

Louis is the author of Bootstrapping Machine Learning and the General Chair of PAPIs.io, the International Conference on Predictive Applications and APIs. Louis works as an independent consultant and helps organizations integrate ML in their domains. He also teaches at University College London School of Management.