As you’ll see when you open your TensorFlow repository in a programming editor or browse the code on GitHub, the core of TensorFlow is implemented in C++ with optional GPU support.

MXNet also supports a broad range of language APIs—Python, C++, Scala, R, JavaScript, Julia, Perl, Go—although its native APIs aren’t as pleasant to work with as TensorFlow’s.

The new data-science tutorial offers tips on using VS Code and the Microsoft Python extension with popular libraries to do tasks like training and evaluating a model, and using TensorFlow to ...

Explaining how to get up to speed with your TensorFlow Lite kit. Check out the 10 minute tutorial video below or jump over to the official Adafruit online resource centre for more details.