Magician’s Corner: 6. TensorFlow and TensorBoard
David C. Vogelsang, Bradley J. Erickson
Abstract
I n a previous article, we provided an introduction to TensorFlow and used it to build a U-Net for the purpose of image segmentation (1). TensorFlow is a popular framework for deep learning applications, developed by Google and first released in 2015. TensorFlow version 2 was released in late 2019 and has several important design changes that make it much more approachable for those new to deep learning, such as direct integration with Keras, while also supporting features for advanced users. The Ten-sorFlow name comes from the fact that tensors are the fundamental computational objects in deep learning: A tensor is an n-dimensional array. Computations on those tensors are expressed as stateful dataflow graphs. TensorFlow enjoys broad hardware and software support, with versions available for tiny microcontrollers up to some of the most powerful computers in the world.