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Machine Learning by Tutorials
The best book on machine learning for iOS. Covers CoreML, Vison, image and sequence classifiers, natural language processing, and more! By Audrey Tam, Matthijs Hollemans, Alexis Gallagher & Chris LaPollo.
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With a free Kodeco account you can download source code, track your progress, bookmark, personalise your learner profile and more!
Create accountAlready a member of Kodeco? Sign in
Sign up/Sign in
With a free Kodeco account you can download source code, track your progress, bookmark, personalise your learner profile and more!
Create accountAlready a member of Kodeco? Sign in
Who is this for?
This books is for the intermediate iOS developer who already knows the basics of iOS and Swift development, but wants to understand how machine learning works.
Covered concepts
- CoreML
- Create ML
- Turi Create and Keras
- Image Classification
- Convolutional Networks
- Sequence Classification
- Text-to-text Transform
Want to know a secret? Machine learning isn’t really that hard to learn. The truth is, you don’t need a PhD from a prestigious university or a background in mathematics to do machine learning. If you already know how to code,...
moreGet started with Machine Learning for Apple and iOS!
Want to know a secret? Machine learning isn’t really that hard to learn. The truth is, you don’t need a PhD from a prestigious university or a background in mathematics to do machine learning. If you already know how to code, you can pick up machine learning quite easily — promise!
This book will get you started with machine learning on iOS and Apple devices. The first bit is a gentle introduction to the world of machine learning and what it has to offer — as well as what its limitations are. In the rest of the book, you’ll look at each of these topics in more detail, until you know enough to make machine learning a useful tool in your software development toolbox.
There are now several high-level Apple frameworks, including Natural Language, Speech, and Vision, that provide advanced machine learning functionality behind simple APIs as part of Apple’s iOS tooling. Whether you want to convert speech to text, recognize language or grammatical structure, detect faces in photos or track moving objects in video, these frameworks have got you covered.
In this book, you’ll learn how to use these tools and frameworks to make your apps smarter. Even better, you’ll learn how machine learning works behind the scenes — and why this technology is awesome.
This book is for all Apple and iOS developers who are interested in learning how to train models, code image recognition systems, learn how natural language processing works, build sequence classifiers and more.
Before You Begin
This section tells you a few things you need to know before you get started, such as what you’ll need for hardware and software, where to find the project files for this book, and more.
Section I: Machine Learning with Images
This section introduces you to the world of machine learning. You’ll get a high level view of what it is, and how it can be used on mobile. You’ll also get a quick primer on using Python for machine learning. You’ll learn how to set up an environment to use tools such as CreateML, Turi Create, and Keras for machine learning. Finally, you’ll learn how to use machine learning techniques to solve problems using images. The topics you’ll explore include image classification, object detection with bounding boxes, and object segmentation.
Section II: Machine Learning with Sequences
In this section, you’ll learn how to apply machine learning to sequential data. You’ll work on a new iOS app which attempts to identify a user’s activity using data from their iPhone’s motion sensors. In the process, you’ll learn how to build a good training dataset, how to create an activity classification model using Turi Create, and how to incorporate your model into an iOS app to support responsive classifications with real-time data.
Section III: Natural Language Processing
In this section, you’ll focus on a specific type of sequential data — natural language text. You’ll learn how to use Apple-provided APIs to perform common language processing tasks. You’ll also learn how to use text with neural networks, and you’ll create a model with Keras that translates text from Spanish to English. Finally, you’ll read about advanced techniques that you can experiment with to improve your model.
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