Marc Päpper - Speeding up the deep learning development life cycle for cancer diagnostics

Speeding up the deep learning development life cycle for cancer diagnostics [EuroPython 2021 - Talk - 2021-07-30 - Parrot [Data Science]] [Online] By Marc Päpper An important, but often overlooked aspect of developing a high-quality deep learning model is the iteration speed. If you can iterate faster, you can try out more ideas and over time you get better results. In this talk, you will learn about the different tricks you can use to train a great machine learning model in a shorter amount of time. In particular, I will discuss how we optimized our deep learning development life cycle at Mindpeak to create robust deep learning models for cancer diagnostics that work in vastly different laboratory settings. The goal of this talk is to point to the most important aspects which you can adjust to speed up the time it takes to go from idea to validated result. I will talk about many different aspects like task prioritization, data processing, communication, GPU paralle