Abstract: Recommendation engines are pretty simple. Or at least, they are made to seem simple by an uncountable number of online tutorials. The only problem: it’s hard to find a tutorial that doesn’t use the ready-made and pre-baked MovieLens dataset. Fine. But, perhaps you’ve followed one of these tutorials and have struggled to imagine how to, or otherwise implement your own recommendation engine on your own data. In this workshop, I’ll show you how to use industry-leading open source tools to build your own engine and how to structure your own data so that it might be “recommendation-compatible”. Note: this workshop will be heavily tilted towards the applied-side of things. Hope you’re ready to get your hands dirty.
Bio: Max is a Lead Instructor at General Assembly and an Apress Author. He likes climbing, making pottery, and fantasy sports. This will be his fifth ODSC!