This talk is an attempt to provide the crucial information needed when you start doing Machine Learning work. Johann du Toit (our speaker) had some *aha* moments throughout his failures, and this talk tries to condense those learnings into one set of slides.
While talking and uncovering these topics in a simple to digest way he'll be sprinkling learnings and demos/examples from his recent work.
Johann will cover a few topics, including:
-> What machine learning actually is, and is not; to level the playing the playing field.
-> The different types of models
-> How you would go about training a model with examples to each
-> How to run your awesome model
We hope the takeaway from this talk will be a structured mindset for those now newly approaching machine learning; be they developers/designers or product managers. You should also be able to walk away with the ability to talk ML and know what to expect when being faced with an ML project.
For the experts, you might at least get to know a few new tools :)
Expect real-time demos and some wackiness sprinkled in.