Justin Revelstoke

A brief introduction to data science and machine learning (5 min)

Brief biography
Definitions, concepts and terminology

The stack (5 min)

Data collection, parsing and processing
Machine learning frameworks
RESTful model interrogation
Designing an intuitive AI interface

Finding the “optimal” recipe by style (5 min)

Analysis, trends and conclusions

The problem space of recipe creation (5 min)

Meet TAP, the open source AI brewing assistant (10 min)

Display TAP’s neural network graph
Ingredient Ad-Libs
Recipe refinement
Novel recipe synthesis​

Challenges (5 min)

Stylistic overlap
Mislabelling
Temperature/Procedural data

The future of brewing with AI (10 min)

Evolutionary styles
Macrobrewing mediocrity
Scheduling optimization
Infection detection
AI driven design