Building Machine Learning Solutions
What does it take to build a solution with machine learning? What does it take to put that solution into production and keep it there? In this session, Rob Harrop explores the engineering and delivery side of building machine learning products that will solve your business problem and delight your customers.
Covering everything from continuous delivery for ML to bias and ethics, from data management to testing. This is not a talk about algorithms or toolkits, this is a talk about the practice of building machine learning solutions using all the engineering best practices you are familiar with.
What will the audience learn from this talk?
- How do I build and test machine learning solutions?
- How do my software engineering skills apply to machine learning?
- How do I go beyond concept and deliver an ML solution into production?
Does it feature code examples and/or live coding?
Prerequisite attendee experience level: