How we made a framework for our ML projects... and we succeeded

Have you had each model developed by your team in its own unique repository, unlike the others? And was it that each of the models had its own versioning and output system, a different way to run training, and even a different way to manage hyperparameters? On the speaker's team, there was. And it hurts.

From the talk you will learn how the team managed to unify the development of all the models and make a convenient framework for it. The speaker will tell you what difficulties they encountered, how they were solved, what the result was and what useful things they learned in the process.