Is machine learning broken by design?!?

Money Money Money … deployment?

… think about tomorrow …

#1: Process

Software Development Process

Machine Learning Process

#2: Conventions / Guidelines

Software Development Conventions

• Git(Hub/Lab)/BitBucket/…
• Intellij/Visual Studio/…
• PyPI/Ubuntu Repo/AppStore/…

Machine Learning Conventions ?

#3 Review & Merge

#4 Tracking

• Code = Yes

• Tests = Yes

• Model = Jain

Result Tracking

1. Copy/Paste from terminal to a file
2. Updated to automatic file appending
3. Log full training to a file

Parameters Tracking

1. Resulting parameters from final model
2. …
3. hmmmm…

Data usage

1. My data haven’t change
2. …
3. hmmmm…

Soups & unfinished

#5 Ship it

Software Deployment

• Jenkins/GoCD/Drone/Sonar/…
• Grafana/ELK/…

Model Deployment

• Custom Code
• Pipelines AirFlow/KubFlow/…

#6 Export & Import

• REST deploy (OK)
• Client/Edge deploy (!?!)
• GDPR ?!?

§1

• Money makes life easier

• $ == true: go into a cloud or buy our own

• $ == false: your are stuck to a lot of manual work

§2

• No gold standard neither for tools nor for a process

• Very fast growing but no conventions and no guidelines