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Natural Language Processing with TensorFlow

Defining Inputs in TensorFlow

Explore different methods to define and feed inputs in TensorFlow 2, including using NumPy arrays, TensorFlow tensors, and the tf.data API. Understand how these input methods integrate with neural network operations, providing a foundation for building NLP models with TensorFlow.

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Overview

Now, we’re returning from our journey into TensorFlow 1 and stepping back to TensorFlow 2. Let’s proceed to the most common elements that comprise a TensorFlow 2 program. If we read any of the millions of TensorFlow clients available on the internet, the TensorFlow-related code all falls into one of these buckets:

  • Inputs: Data used to train and test our algorithms.
  • Variables: Mutable tensors,
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