This post summarizes and links to a great multi-part tutorial series on learning the TensorFlow API for building a variety of neural networks, as well as a bonus tutorial on backpropagation from the beginning.
By Erik Hallström, Deep Learning Research Engineer.
Editor’s note: The TensorFlow API has undergone changes since this series was first published. However, the general ideas are the same, and an otherwise well-structured tutorial such as this provides a great jumping off point and opportunity to consult the API documentation to identify and implement said changes.
Schematic of a RNN processing sequential data over time.