English | MP4 | AVC 1280×720 | AAC 44KHz 2ch | 1h 25m | 601 MB
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.
Topics include:
- 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
Table of Contents
Introduction
1 Welcome
2 What you should know
3 Using the exercise files
Machine Learning – Basics and Tools
4 Machine learning and Core ML
5 Custom models with Turi Create
6 Your machine learning setup
7 Getting comfortable with Python part 1
8 Getting comfortable with Python part 2
Cats vs. Dogs – Create an ML Model
9 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
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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