Neural network models and deep learning - a primer for biologists
It serves as an educational primer for biologists to grasp deep learning concepts, with no new research contributions, making it incremental in nature.
The paper provides an introductory overview of neural network models and deep learning for biologists, explaining their origins, basic architectures, and potential applications in understanding brain computations.
Originally inspired by neurobiology, deep neural network models have become a powerful tool of machine learning and artificial intelligence, where they are used to approximate functions and dynamics by learning from examples. Here we give a brief introduction to neural network models and deep learning for biologists. We introduce feedforward and recurrent networks and explain the expressive power of this modeling framework and the backpropagation algorithm for setting the parameters. Finally, we consider how deep neural networks might help us understand the brain's computations.