Release TensorFlow 2.0.0 · tensorflow/tensorflow
Release 2.0.0 Major Features and Improvements TensorFlow 2.0 focuses on simplicity and ease of use, featuring updates like: Easy model building with Keras and eager execution. Robust model deployment in production on any platform. Powerful experimentation for research. API simplification by reducing duplication and removing deprecated endpoints. For details on best practices with 2.0, see the Effe
tfjs-models/posenet/demos at master · tensorflow/tfjs-models · GitHub
PoseNet Demos Contents Demo 1: Camera The camera demo shows how to estimate poses in real-time from a webcam video stream. Demo 2: Coco Images The coco images demo shows how to estimate poses in images. It also illustrates the differences between the single-person and multi-person pose detection algorithms. Setup cd into the demos folder:
Release TensorFlow 1.8.0 · tensorflow/tensorflow
Release 1.8.0 Major Features And Improvements Can now pass tf.contrib.distribute.MirroredStrategy() to tf.estimator.RunConfig() to run an Estimator model on multiple GPUs on one machine. Add tf.contrib.data.prefetch_to_device(), which supports prefetching to GPU memory. Added Gradient Boosted Trees as pre-made Estimators: BoostedTreesClassifier, BoostedTreesRegressor. Add 3rd generation pipeline c
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GitHub - tensorflow/text: Making text a first-class citizen in TensorFlow.
https://github.com/tensorflow/swift/blob/master/docs/DifferentiableFunctions.md
https://github.com/tensorflow/swift/blob/master/docs/DifferentiableTypes.md
