Diagram showing the graph for this model in tensorboard. How to run this code. Since this is the python code and both restore_model_tensorflow.py and save_model_tensorflow.py are independent of each ...

The custom inference model must be in the form of a TensorFlow Lite (.tflite) file. For this example, we will use the same object detection model that is used in Google's example TensorFlow Object ...

TensorFlow Model Analysis (TFMA) is a tool that helps you evaluate and validate your machine learning models using various metrics and visualizations. It can help you identify and debug issues ...

Building a new model on top of the pre-trained base comes next after the base model has been loaded and the data is ready. Usually, this entails adding a few layers particular to your task: from ...

TensorFlow has become the most popular tool and framework for machine learning in a short span of time. It enjoys tremendous popularity among ML engineers and developers. According to the Hacker ...

TensorFlow recently launched its latest pose detection model, MoveNet, with a new pose-detection API in TensorFlow.js. Both the models run faster than real time (i.e.,30+ FramesPerSecond) on most ...

TensorFlow recently launched its first 3D model in TensorFlow.js pose detection API. The new model opens up doors to new design opportunities for applications such as fitness, medical motion capture, ...