Project Description

Smart homes, self-driving cars, Siri, Alexa – some prevalent examples of how machine learning and artificial intelligence have become part of our daily life. Wouldn’t it be cool to understand the concepts behind these complex topics?

This course teaches you how to integrate machine learning into your iOS, macOS or watchOS apps. We’re going to demystify what machine learning is by investigating how it works and delving into the most important concepts.

This course is going to familiarize you with common machine learning tasks. We’ll focus on practical applications, using hands-on Swift code examples.

We’ll delve into advanced topics like synthetic vision and natural language processing. You’ll apply what you’ve learned by building iOS applications capable of identifying faces, barcodes, text and rectangular areas in photos in real-time.

You’ll learn how to train machine learning models on your computer. You’re going to develop several smart apps, including a flower recognizer and an Amazon review sentiment analyzer.
And there’s a lot more!

And no worries — we introduce each concept using simple terms, avoiding confusing jargon.

Topics include:

  • Understanding the machine learning frameworks provided by Apple
  • Natural language text processing using the NaturalLanguage framework
  • Setting up a Core ML project in Xcode
  • Image analysis using Vision
  • Training an image classifier on your computer using CreateML
  • Determining the tonality of an Amazon product review

Machine Learning with CoreML 2 and Swift is the perfect course for you if you’re interested in machine learning, or if you’re looking to switch into an exciting new career track.