Go from zero to hero with Machine Learning and Core ML

Learn to develop AI-based apps for iOS and train various types of ML models. Now it is fully updated for Xcode 12, iOS 14, and Swift 5.3.

A Comprehensive Guide to Machine Learning, Core ML, Python, and Cloud-based ML

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.

This book covers Core ML in-depth. You will learn how to create and deploy your own machine learning model. On top of that, you will learn 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.

By going through this book, you’ll also become proficient with Python, the language that’s most frequently used for machine learning. Plus, you would have created a handful of ready-to-use apps such as barcode scanners, image classifiers, and language translators. Most importantly, you will master the ins-and-outs of Core ML.

What you'll learn

Chapter 1 - Machine Learning at a Glance
You will learn about machine learning from a birds-eye view and its applications, different model types, and machine learning APIs.
Chapter 2 - Building an Image Classification App
You will build your own image classification app and get a taste for this book's hands-on approach.
Chapter 3 - A Primer on Python and Jupyter Notebook
You will dive straight into Python and explore Jupyter Notebooks to prepare you to learn Turi Create.
Chapter 4 - Training Your Own Image Classifier
You'll learn about image classification models, what they're useful for, and how you can train your own image classification models for your apps.
Chapter 5 - Natural Language Processing
You'll learn about linguistics in machine learning, including natural language processing, text classification, and word tagging.
Chapter 6 - Sound Classification Models
You'll learn how to use Create ML to train your own sound classifier using the IRMAS audio dataset and learn how to integrate it in an iOS app.
Chapter 7 - Cloud-Based Machine Learning with Firebase
You will get a fresh perspective on mobile machine learning by building a couple of apps using a cloud-based API called Firebase.
Chapter 8 - Updatable ML Models for On-Device Training
You will learn all about updatable models and how they work. You will also explore tools available on the internet to help you train, source, and interact with updatable models.
Chapter 9 - Action Classification and Style Transfer
You will learn about action classification and style transfer, two emerging technologies which have the potential to revolutionize machine learning's role in various fields from gaming to art.
Chapter 10 - Supercharge ML Workflow with these Tips and Tricks
You will reflect on what you've learned throughout this book and explore additional tips and tricks to supercharge your machine learning workflow.

Meet the Author

Vardhan Agrawal is a self-taught developer who works primarily with Swift and iOS development. Vardhan has a penchant for turning his far-fetched ideas into scientific realities. Vardhan has also developed several ingenious products to better the lives of people around the world. 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 his nonprofit, TheOpenCode Foundation.
Vardhan Agrawal
iOS Developer

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