First of all, let’s look at the topics that we will cover in this blog:

  1. What is TensorFlow?
  2. How does TensorFlow work?
  3. Why is TensorFlow popular?
  4. Components of TensorFlow
  5. TensorFlow Architecture for Building Models
  6. Basics of TensorFlow

What is TensorFlow?

TensorFlow is one of the most in-demand tools used by ML/AI Engineers. It is an open-source framework developed by Google, which is used to build various Machine Learning and Deep Learning models.

TensorFlow helps us train and execute neural network image recognition, natural language processing, digit classification, and many more. Also, using the same models used for development, TensorFlow facilitates the estimation of the output at various scales.

The main objective of using TensorFlow is not just the development of a deep neural network. But, it is focused to reduce the complexity of implementing computations on large numerical datasets. Since Deep Learning models require a lot of computation for attaining accuracy, companies started using TensorFlow. Thus, Google made TensorFlow available to everyone.

#tensorflow #deep-learning #data-science #python #developer

What is TensorFlow? - Introduction to TensorFlow
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