If you are adept at Python and remember your high school algebra, you might enjoy [Oliver Holloway’s] tutorial on getting started with Tensorflow in Python.

The tutorial that the TensorFlow authors offer for beginners goes step-by-step through some simple TensorFlow models. Among other things it teaches you about the high-level tf.estimator API for ...

At the 2019 TensorFlow Dev Summit today, Google announced a number of updates for its open-source machine learning library aimed at research and production. The TensorFlow 2.0 alpha provides a ...

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.

TensorFlow is a Python-friendly open source library for developing machine learning applications and neural networks. Here's what you need to know about TensorFlow.

The Next Step As we said, the code for the binary counter neural network is on our github page. You can start with that, start from scratch, or use any of the many tutorials on the TensorFlow website.

TensorFlow 2.0 fires up AI models much faster than previous versions, which lets engineers try out different model variations with shorter delays between test runs.

TensorFlow 2.0 will also feature eager execution by default -- this means ops will run immediately upon calling them.

This is new: TensorFlow 2.18 integrates the current version 2.0 of NumPy and, with Hermetic CUDA, will no longer require local CUDA libraries during the build.