Free

Back-of-the-Envelope Calculation For Machine Learning Projects

Actions and Detail Panel

Free

Event Information

Share this event

Date and time

Location

Location

Online event

Event description
Confirming that our future ML project is worthwhile - Larysa Visengeriyeva

About this event

One of the best practices that we know from great engineers is the back-of-the-envelope calculation to estimate costs and resources. I believe that in Machine Learning Engineering, we all would benefit from such a “back-of-the-envelope calculation” skill to create a prototype of an ML Project. We need to confirm - as cheaply as possible - that our future ML project is worthwhile, that it will solve my business problem, and that costs and resources are feasible. In my talk, I suggest a design toolkit for ML projects to perform such rough prototyping by using three canvases: Machine Learning Canvas, Data Landscape Canvas, and MLOps Stack Canvas.

About the speaker:

Larysa is working at INNOQ and her current interest is the intersection between Sofware Engineering and Machine Learning - MLOps. She holds a PhD in the field of Augmented Data Cleaning.

DataTalks.Club is the place to talk about data. Join our slack community!

Share with friends

Date and time

Location

Online event

Organizer DataTalks.Club

Organizer of Back-of-the-Envelope Calculation For Machine Learning Projects

Save This Event

Event Saved