TensorFlow 2.0 Computer Vision Cookbook

Chapter 11: Streamlining Network Implementation with AutoML

Computer vision, particularly when combined with deep learning, is a field that's not suitable for the faint of heart! While in traditional computer programming, we have a limited set of options for debugging and experimentation, this is not the case in machine learning.

Of course, the stochastic nature of machine learning itself plays a role in making the process of creating a good enough solution difficult, but so do the myriad of parameters, variables, knobs, and settings we need to get right to unlock the true power of a neural network for a particular problem.

Selecting a proper architecture is just the beginning because we also need to consider preprocessing techniques, learning ...