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Mastering Machine Learning with Core ML and Python (Early Access)

*** This is the alpha version of Mastering Machine Learning with Core ML and Python. We are still reviewing and editing the content, so the final release will be a bit different from the current version.

All the source code and projects are intended to work for Xcode 11 and iOS 13. We are hard at work updating the book for Xcode 12 and iOS 14. We target to release the official version by Oct. ***


About the Book

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Machine learning, now more than ever, plays a pivotal role in almost everything we do in our digital lives. Whether it’s interacting with a virtual assistant like Siri or typing out a message to a friend, machine learning is the technology facilitating those actions. It’s clear that machine learning is here to stay, and as such, it’s a vital skill to have in the upcoming decades. Since more users will be reliant on such technology, it’s important to dive in and hone your machine learning skills to make your apps more engaging, fun, and useful for your users!

Core ML is Apple’s end-to-end platform which allows for fast, powerful, and on-device machine learning in your iOS apps. Core ML is a Swift-based framework which allows developers to deploy lightweight models and ship them with their apps. As Core ML continually gets better, more developers will begin using it because of it’s close-knit compatibility with Apple’s hardware.

In this book, you'll not only learn Core ML in-depth, but the author will also be teaching you about Turi Create, Create ML, Keras, Firebase, and Jupyter Notebooks, just to name a few. These are a few examples of professional tools which are staples for many machine learning experts. Throughout this book, you’ll also become proficient with Python, the language that’s most frequently used for machine learning. 

By the end of the book, you would have created a handful of ready-to-use apps such as barcode scanners, image classifiers, and language translators. And, you would have mastered the ins-and-outs of Core ML!


About the Author

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Vardhan Agrawal is a self-taught developer who works primarily with Swift and iOS development. Some of the other languages Vardhan is well-versed with include Java, Javascript, Objective-C, HTML, and CSS. Not only does he tinker with new projects and ideas, but he also makes it possible for others to do the same by teaching others to code. Vardhan is a part of the tutorials team at raywenderlich.com, Envato Tuts, Heartbeat by Fritz, and freeCodeCamp. He has also been recognized for his dedication to social good. He helps disadvantaged students learn to code through TheOpenCode Foundation.

He is also active in the open-source community and has been personally recognized by GitHub for his contributions. Vardhan has also developed several ingenious products to better the lives of people around the world. Whether it’s helping the local city solve their chronic street light problem with drones, developing a novel blood pressure monitoring device, or creating a breakthrough in space medicine, Vardhan has a penchant for turning his far-fetched ideas into scientific realities. When he’s not coding, you can find him producing and editing videos, working on getting his private pilot license, or playing the violin.

You can reach him via LinkedIn at https://www.linkedin.com/in/vardhanagrawal or Twitter at https://twitter.com/vhanagwal. He can also be found on his website, www.vardhanagrawal.com.


Table of Contents

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Chapter 1 - Machine Learning at a Glance

Chapter 2 - Building an Image Classification App

Chapter 3 - A Primer on Python and Jupiter Notebook

Chapter 4 - Training Your Own Image Classifier

Chapter 5 - Natural Language Processing

Chapter 6 - Sound Classification Models

Chapter 7 - Cloud-Based Machine Learning with Firebase

Chapter 8 - Updatable ML Models for On-Device Training

Chapter 9 - Action Classification and Style Transfer

Chapter 10 - Supercharge ML Workflow with these Tips and Tricks


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  • Over 300 page eBookPDF/ePub/Mobi/HTML
  • Xcode projectsFull source code for download

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Mastering Machine Learning with Core ML and Python (Early Access)

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