Tl;dr: this wiki page has everything you need to get started.

ZeroCostDL4Mic is a collection of self-explanatory Jupyter Notebooks for Google Colab that features an easy-to-use graphical user interface. They are meant to quickly get you started on learning to use deep-learning for microscopy. Google Colab itself provides the computations resources needed at no-cost. ZeroCostDL4Mic is designed for researchers that have little or no coding expertise to quickly test, train and use popular Deep-Learning networks.

Running a ZeroCostDL4Mic notebook	Example data in ZeroCostDL4Mic	Romain's talk @ Aurox conference

Any researcher interested in microscopy, independent of their background training. ZeroCostDL4Mic is designed for anyone with little or no coding expertise to quickly test, train and use popular Deep-Learning networks used to process microscopy data.

This project initiated as a collaboration between the Jacquemet and Henriques laboratories, considerably expanding with the help of laboratories spread across the planet. There is a long list of contributors associated with the project acknowledged in our preprint and the wiki page.

Lucas von Chamier, Johanna Jukkala, Christoph Spahn, Martina Lerche, Sara Hernández-pérez, Pieta Mattila, Eleni Karinou, Seamus Holden, Ahmet Can Solak, Alexander Krull, Tim-Oliver Buchholz, Florian Jug, Loïc Alain Royer, Mike Heilemann, Romain F. Laine, Guillaume Jacquemet, Ricardo Henriques. ZeroCostDL4Mic: an open platform to simplify access and use of Deep-Learning in Microscopy. bioRxiv, 2020. DOI: https://doi.org/10.1101/2020.03.20.000133