The TensorFlow API is computation using data flow graphs for scalable machine learning. It is an open source software library for numerical computation using data flow graphs. This architecture lets you deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device without rewriting code. It also includes TensorBoard, a data visualization toolkit. TensorFlow is a scalable open-source machine learning library for research and production.
The following is a list of how-to and tutorial content that matched your search term. ProgrammableWeb's how-to content comes from two sources; full-blown tutorials that we publish ourselves and other highly relevant tutorials that we find elsewhere on the Web. This list represents on combination of both tutorial types and if you go to ProgrammableWeb's API University, you'll not only be able to find more, they are organized based on your role (API providers or developers who consumes APIs). If you know of a tutorial that would be of interest to the ProgrammableWeb community, we'd like to know about it. Be sure to check our guidelines for making contributions to ProgrammableWeb.
When Google opened its Tensor Flow machine learning (ML) tech, it also unleashed a tidal wave of possibilities, potentially triggering a tipping point as businesses begin to understand what ML can do for them. But for many ML remains an enigma. This tutorial is for those of us who are such mortals.