TensorFlow also has a broad library of pre-trained models available for use in your projects. Code from the TensorFlow Model Garden provides examples of best practices for training your own models.

TensorFlow's mobile and IoT toolkit, TensorFlow Lite, supports post-training quantization of models, which can reduce model size up to 4x and increase inference speed up to 1.5x.

TensorFlow.js is a JavaScript-based framework to run machine learning models within the browser. Any modern browser can run the TensorFlow model with no changes to the code.

Google has announced the TensorFlow Lite Model Maker. TensorFlow Lite is an open-source deep learning framework for on-device inference. The new tool is designed to adapt machine learning models ...

Google today announced TensorFlow Lite Model Maker, a tool that adapts state-of-the-art machine learning models to custom data sets using a technique known as transfer learning. It wraps machine ...

If you prefer to draw boxes instead of writing code, you may have tried IBM’s Node-RED to create logic with drag-and-drop flows. A recent [TensorFlow] video shows an interview between [Jason … ...

Prior versions of the image captioning model took three seconds per training step on an Nvidia G20 GPU, but the version open sourced today can do the same task in a quarter of that time, or just 0 ...

Google LLC today announced a new tool called TensorFlow Lite Model Maker, which uses a technique known as transfer learning to adapt machine learning models to custom data sets. TensorFlow Lite is ...

Google today is announcing the release of version 0.8 of its TensorFlow open-source machine learning software. The release is significant because it supports the ability to train machine learning ...

“It’s very time-consuming and arduous,” says Peterson. TensorFlow helps the team get to a working result faster. “You can feed a TensorFlow model 1,000 images of a cat and 1,000 of a dog.