Book Image

Machine Learning with Core ML

Book Image

Machine Learning with Core ML

Overview of this book

Core ML is a popular framework by Apple, with APIs designed to support various machine learning tasks. It allows you to train your machine learning models and then integrate them into your iOS apps. Machine Learning with Core ML is a fun and practical guide that not only demystifies Core ML but also sheds light on machine learning. In this book, you’ll walk through realistic and interesting examples of machine learning in the context of mobile platforms (specifically iOS). You’ll learn to implement Core ML for visual-based applications using the principles of transfer learning and neural networks. Having got to grips with the basics, you’ll discover a series of seven examples, each providing a new use-case that uncovers how machine learning can be applied along with the related concepts. By the end of the book, you will have the skills required to put machine learning to work in their own applications, using the Core ML APIs
Table of Contents (16 chapters)
Title Page
Packt Upsell
Contributors
Preface
Index

Working with probabilistic results


As alluded to at the beginning of this chapter and seen firsthand in the previous section, working with machine learning models requires a set of new techniques and strategies to deal with uncertainty. The approach taken will be domain-specific, but there are some broad strategies that are worth keeping in mind, and that's what we will cover in this section in the context of the example project of this chapter. 

Improving the model

The first is improving the model. Of course, there may be limitations depending on the source of the model and dataset, but it's important to be able to understand ways in which the model can be improved as its output directly correlates to the quality of the user experience.

In the context of this project, we can augment the model using an existing pre-trained image classifier as the encoder, as mentioned earlier. This not only fast-tracks training, providing more opportunities to iterate, but also is likely to improve performance...