Complementary Libraries to TensorFlow 2.x

Abstract

Now that we covered the basics of machine learning and deep learning, we can slowly move on to the applied side of deep learning. As you know, every machine learning application, including deep learning applications, has a pipeline consisting of several steps. TensorFlow offers us several modules for all these steps. Even though TensorFlow is very powerful for model building, training, evaluation, and making predictions, we still need other complementary libraries for certain tasks, especially for data preparation. Although the potential libraries you may use in a deep learning pipeline may vary to a great extent, the most popular complementary libraries are as follows: