Better Brewing through Data Science and Machine Learning

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