Introduction
Machine learning is one of the hottest trends in computing and deals with the problem of creating computer programs that can generalize and predict information reliably, quickly, and with accuracy, resembling what a human would do with similar information. With the recent hype in mainstream media around novel applications of machine learning, you may be inclined to think that machine learning is a relatively new discipline, but that is far from the truth. In fact, machine learning has been around for several decades, and it is because of recent advances in storage, processor, and GPU technology that it is possible to build and deploy machine learning systems at scale and get results in real time.
This book is targeted at intermediate/advanced iOS developers who are looking to come to grips with the fundamentals of machine learning, learn about some of the common tools used by data scientists, and learn how to build and deploy models into their iOS applications. This book at all times attempts to balance theory and practice, giving you enough visibility into the underlying concepts while providing you with the best practices and practical advice that you can apply to your workplace right away.
Machine learning is a rapidly evolving field. I have made every attempt to keep the content up-to-date and relevant. Even though this makes the book susceptible to being outdated on a few rare instances, I am confident the content will remain useful and relevant through the ...
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