Machine Learning with Core ML 2 and Swift 5 - A Beginner-Friendly Guide

Karoly Nyisztor, Senior Software Engineer, Instructor

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43 Lessons (2h 9m)
    • 1. Machine Learning with Core ML 2 and Swift

      1:30
    • 2. 1.1 Introduction - Prerequisites

      1:35
    • 3. 1.2 What is Machine Learning?

      2:27
    • 4. 1.3 Supervised and Unsupervised Machine Learning

      2:00
    • 5. 1.4 The Machine Learning Model

      2:43
    • 6. 1.5 iOS and Machine Learning

      1:05
    • 7. 1.6 Exercise Files

      1:00
    • 8. 2.1 iOS Machine Learning Architecture

      1:15
    • 9. 2.2 The Core ML Framework

      1:13
    • 10. 2.3 Natural Language Processing

      1:25
    • 11. 2.4 The Vision Framework

      1:47
    • 12. 2.5 The GamePlayKit Framework

      3:08
    • 13. 3.1 Natural Language Text Analysis

      1:23
    • 14. 3.2 Recognizing the Dominant Language of a Text

      6:06
    • 15. 3.3 Enumerating the Words in a Text

      4:13
    • 16. 3.4 Identifying Parts of Speech

      3:22
    • 17. 3.5 Identifying People, Places and Organizations

      2:16
    • 18. 4.1 Image Analysis with the Vision Framework

      0:52
    • 19. 4.2 The Starter App

      3:45
    • 20. 4.3 Analyzing Still Images using Vision

      1:30
    • 21. 4.4 Implementing the Image Request Handler

      7:05
    • 22. 4.5 Detecting Rectangular Areas - The Image Analysis Request

      6:30
    • 23. 4.6 Converting Coordinates Between Quartz 2D and UIKit

      3:55
    • 24. 4.7 Visualizing the Detected Rectangles

      6:35
    • 25. 4.8 Recognizing Text, Faces and Barcodes in Still Images

      4:25
    • 26. 5.1 Training a Flower Classifier on Your Computer using Create ML

      0:42
    • 27. 5.2 Recognizing Flowers - Preparing the Training Data

      2:24
    • 28. 5.3 Training an Image Classifier in a Playground

      4:31
    • 29. 5.4 Recognizing Flowers - the Starter App

      2:02
    • 30. 5.5 Integrating the Flower Classifier Model

      4:00
    • 31. 5.6 Displaying Predictions

      3:00
    • 32. 5.7 Picking an Image

      2:37
    • 33. 5.8 Performing the Image Analysis Request

      3:00
    • 34. 5.9 The Flower Recognizer App in Action

      2:44
    • 35. 6.1 Determining the Tonality of a Review

      0:36
    • 36. 6.2 Preparing the Training Data

      1:23
    • 37. 6.3 Training a Text Classifier in a Playground

      6:03
    • 38. 6.4 Creating the MLTextClassifier

      5:16
    • 39. 6.5 Saving the Core ML Model

      2:57
    • 40. 6.6 Laying Out the User Interface of the Review Classifier App

      2:54
    • 41. 6.7 Integrating the Review Classifier Model

      6:42
    • 42. 6.8 Testing the Review Classifier App

      4:25
    • 43. Goodbye!

      1:03

About This Class

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 apps. We're going to demystify what machine learning is by investigating how it works and delving into the most important concepts.

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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.

Student reviews from our other courses

“This course was easy to understand and I feel like I know the basics and where to go next.” - Kyra Morris

“Abstract stuff distilled into bite-size relatable information.” - Brian McPherson

“Great to Go Course! Masterpiece in info for the Software Development industry.” - Prabhakar Kumar

“I really enjoyed the variety of topics and the concise style.” - Monique

About the Author

Károly Nyisztor is a veteran mobile developer and instructor.

He has built several successful iOS apps and games—most of which were featured by Apple—and is the founder at LEAKKA, a software development, and tech consulting company. He's worked with companies such as Apple, Siemens, SAP, and Zen Studios.

Currently, he spends most of his days as a professional software engineer and IT architect. In addition, he teaches object-oriented software design, iOS, Swift, Objective-C, and UML. As an instructor, he aims to share his 20+ years of software development expertise and change the lives of students throughout the world. He's passionate about helping people reveal hidden talents, and guide them into the world of startups and programming.

You can find his courses and books on all major platforms including Amazon, Lynda, LinkedIn Learning, Pluralsight, Udemy, and iTunes.

You’ll Get Premium Support 

As a student of this course, you’ll get personalized attention and support.

Go ahead and click the enroll button. 
See you in the first lesson!