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Life after the model

Convolutional neural network is ready, F1 score calculated and ROC curve drawn. So you have a model. This tale is about what happens next: when and how to cleanse the model, how do push it into production and what defines quality for the model. I will show it using one of the projects we deployed here at AirHelp. I will also try to show a few tips & tricks that helps me manage Machine Learning projects.

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Data
About the speaker
Michał Jakóbczyk
Software Engineering Director at Airhelp
Primarily I'm a Software Engineer. For last fifteen years doing Big Data, data analysis, machine learning, product and project management. For last several years focused…
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