TensorFlow 2 is a rich development ecosystem composed of two main parts: Training and Serving. Training consists of a set of libraries for dealing with datasets (tf.data), a set of libraries for building models, including high-level libraries (tf.Keras and Estimators), low-level libraries (tf.*), and a collection of pretrained models (tf.Hub). Training can happen on CPUs, […]
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