Deep learning is increasingly used to automate image-based tasks such as detecting, counting, or classifying specimens, but the underlying methods can feel opaque to non-specialists. This talk introduces the core principles behind deep neural networks and how they are applied to image analysis. We will go through the basics of machine learning and build valid intuitions for how and why recent deep learning models work.