From a model to production: Software-engineering best-practices

Published on 23 November 2017, in #talks, #data-engineering, #python

At PyData Warsaw 2017 and Prague Hadoop Meetup 2017 I talked about best-practices for putting a prototype of a machine-learning model or a data application into production. I tried my best to cover principles agnostic to a language or a technology. I see now I put perhaps too much detail in the slides & I was also more opinionated back then.

Slide deck: http://talks.marcel.is/hugcz2017-sebp

Video from the PyData Warsaw:

• ← Previous post: Should you hire a data engineer instead of a data scientist?
• → Next post: Which task do you resent the most today?

This blog is written by Marcel Krcah, an independent consultant for product-oriented software engineering. If you like what you read, sign up for my newsletter