Now that you have an understanding of the foundations of deep learning, you should be well placed to apply this knowledge to specific learning problems that you are interested in. In this chapter, we have developed an out-of-the-box solution for image classification using pretrained models. As you have seen, this is quite simple to implement, and can be applied to almost any image classification problem you can think of. Of course, the actual performance in each situation will depend on the number and quality of images presented, as well as the precise tuning of the hyperparameters associated with each model and task.
You can generally get very good results on most image classification tasks by simply running the pretrained models with default parameters. This requires no theoretical knowledge, apart from installing the programs' running environment. You will find...