Machine Learning for iOS Developers
1h 26mAdvanced2018-04-04
Authors

Brian Advent
Software Developer, Educator, Mathematician
Course details
Do you want to build custom machine learning models to enhance your iOS apps? Even if you're not a machine learning expert, Core ML makes it easy to integrate an existing machine learning model into an iOS application. And with Turi Create, Apple also provides a Python framework that simplifies the development of custom machine learning models. This course provides an introduction to machine learning and the Core ML framework, and covers how to build your own custom machine learning model and integrate it into an iOS app. Upon wrapping up this course, you will have built an image classifier that can distinguish cats from dogs in a provided picture.
Learning objectives
Using Turi Create to create custom models
Getting comfortable with Python
Preparing data for Turi Create
Creating a machine learning model with Turi Create
Implementing an image picker controller
Using Core ML and the Vision framework for image classification
Learning objectives
Using Turi Create to create custom models
Getting comfortable with Python
Preparing data for Turi Create
Creating a machine learning model with Turi Create
Implementing an image picker controller
Using Core ML and the Vision framework for image classification
Skills covered
iOSMachine LearningAppleArtificial Intelligence (AI)Learning
Concepts
0. Introduction
- 01 - Welcome
- 02 - What you should know
- 03 - Using the exercise files
1. Machine Learning - Basics and Tools
- 04 - Machine learning and Core ML
- 05 - Custom models with Turi Create
- 06 - Your machine learning setup
- 07 - Getting comfortable with Python, part 1
- 08 - Getting comfortable with Python, part 2
2. Cats vs. Dogs - Create an ML Model
- 09 - The data set we work with
- 10 - Work with Turi Create
- 11 - Prepare the data for Turi Create
- 12 - Create an ML model with Turi Create
3. Dogs vs. Cats - The iOS App
- 13 - Our sample app - Dogs vs. Cats
- 14 - A quick look around the Xcode project
- 15 - Implement an image picker controller
- 16 - The Vision framework and Core ML
- 17 - An animal detector powered by Vision
- 18 - Our machine learning model in action
Conclusion
- 19 - Next steps
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