  Deep learning is transforming most areas of science and technology, including
electron microscopy. This review paper offers a practical perspective aimed at
developers with limited familiarity. For context, we review popular
applications of deep learning in electron microscopy. Afterwards, we discuss
hardware and software needed to get started with deep learning and interface
with electron microscopes. We then review neural network components, popular
architectures, and their optimization. Finally, we discuss future directions of
deep learning in electron microscopy.
