Model Maker, which currently only supports image and text classification use cases, works with many of the models in TensorFlow Hub, Google’s library for reusable machine learning modules.

The world of artificial intelligence (AI) is divided into two main camps: open-source AI and corporate AI. Both have their ...

The basic idea of TensorFlow Lite is that you train a full-blown TensorFlow model and convert it to the TensorFlow Lite model format. Then you can use the converted file in your mobile application ...

We will create a Deep Neural Network python from scratch. We are not going to use Tensorflow or any built-in model to write the code, but it's entirely from scratch in python. We will code Deep Neural ...

Model File: A model file format based on FlatBuffers, optimized for speed and size. TensorFlow Lite supports hardware acceleration with the Android Neural Networks API.

TensorFlow is an open source software library developed by Google for numerical computation with data flow graphs. This TensorFlow guide covers why the library matters, how to use it and more.

TensorFlow Model Optimization introduced full post-training integer quantization last summer, but quantization-aware training was only available as an unofficial "contrib" package.

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 ...

Discover how to build an automated intent classification model by leveraging pre-training data using a BERT encoder, BigQuery, and Google Data Studio.