The difference between training and inference is similar to that of a student being taught something like algebra at school and then applying it in the real world. In school, the student is given numerous exercises; for each exercise, the student attempts the question and hands his/her answer over to the teacher, who provides feedback indicating whether it is correct or not. Initially, this feedback is likely to be skewed toward the student being wrong more often than right, but after many attempts, as the student starts building his/her understanding of the concepts, the feedback shifts towards mostly being right. At this point, the student is considered to have sufficiently learned algebra and is able to apply it to unseen problems in the real world, where he/she can be confident of the answer based on his/her exposure to the...
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Book Overview & Buying
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Table Of Contents
Machine Learning with Core ML
By :
Machine Learning with Core ML
By:
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 (12 chapters)
Preface
Free Chapter
Introduction to Machine Learning
Introduction to Apple Core ML
Recognizing Objects in the World
Emotion Detection with CNNs
Locating Objects in the World
Creating Art with Style Transfer
Assisted Drawing with CNNs
Assisted Drawing with RNNs
Object Segmentation Using CNNs
An Introduction to Create ML
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