Complete iOS Machine Learning Masterclass

About Course

The most comprehensive course on Machine Learning for iOS development. Master building smart apps iOS Swift 4

Categories Development

Course Curriculum

1. Getting started

001 About Your Instructor and Course Overview

00:00
002 About Machine Learning

00:00
003 Activity_ Playing with Machine Learning Style Transfer

00:00

2. Optional – iOS Fundamentals

3. Optional – Machine Learning Concepts

4. iOS Machine Learning With Photos

016 About this section – coreML with Photos

00:00
017 Demo of project using coreML on photos

00:00
018 About ML model and Neural Networks

00:00
019 Project_ Create the xcode project

00:00
020 Project_ How to add ML models to xcode projects

00:00
021 Project_ How to get pre-made ML models for iOS

00:00
022 Project_ How to use ML models with images (part 1)

00:00
023 Project_ How to use ML models with images (part 2)

00:00
024 Project_ Programming the VN request callback method

00:00
025 Testing different ML models

00:00
026 Exercise_ Models with Images input

00:00
027 Solution_ Models with Images input

00:00
028 Summary_ coreML Vision with Photos

00:00

5. coreML All about custom models

6. CoreML with Data Set models

035 Introduction to Working with Data sets

00:00
036 Project_ Create xcode project and add iris model

00:00
037 Project_ ML dataset project User Interface

00:00
038 Project_ Properties and picker delegate methods

00:00
039 Project_ Pickerview data source methods

00:00
040 Project_ Coding prediction for data sets

00:00
041 Project_ Code improvements

00:00
042 Important data set models information

00:00

7. Project: coreML with Video Camera

043 About CoreML with Video Camera

00:00
044 Project_ Create xcode project and add VGG16 model

00:00
045 Project_ Building the user interface

00:00
046 Project_ Video Stream variables setup

00:00
047 Project_ Program camera feed

00:00
048 Project_ Capture image from video stream for ML model

00:00
049 Project_ Programming the ML prediction launch

00:00
050 Project_ Processing the ML model output

00:00
050 Project_ Processing the ML model output

00:00
051 Testing the live camera feed with VGG model

00:00

8. END: iOS coreML fundamentals

9. Optional – Going the extra mile

10. Optional – Numerous Model Conversions

11. Advanced Vision Techniques: Face Detection

12. Optional – Advanced Face Features Detection

071 About Advanced Face Feature Recognition

00:00
072 Locate face position and area (part 1 of 2)

00:00
073 Locate face position and area (part 2 of 2)

00:00
074 Code to detect Face features eyes nose lips

00:00
075 face features part 2

00:00
076 face features part 3

00:00
077 face features part 4

00:00
078 Activity – draw all face features in blue

00:00
079 Activity Solution

00:00

13. Advanced Text Detection Techniques

14. Object Tracking (advanced)

087 Demo_ Object Tracking Project

00:00
088 Create Object Tracking Project and UI

00:00
089 Program Video Camera Stream

00:00
090 Coding the camera stream launch

00:00
091 Capturing Data and Perform Tracking Request

00:00
092 Coding the tracking request completion handler

00:00
093 Program the object tracking launch

00:00
094 Final Modifications

00:00
095 Final Project Demo

00:00

€69.89

Course Details

Level: All Levels

Duration: 0

Enrolled:0

Last Updated:February 5, 2022

Complete iOS Machine Learning Masterclass

About Course

Course Curriculum

1. Getting started

001 About Your Instructor and Course Overview

002 About Machine Learning

003 Activity_ Playing with Machine Learning Style Transfer

2. Optional – iOS Fundamentals

004 About this section – start iOS

005 Download and install xcode for iOS 11.mp4

006 Get the iOS developer license.mp4

007 How to use a MAC on Windows PC or Linux.mp4

008 How to install iOS 11 on your iPhone or iPad

009 Use the Xcode interface

010 Xcode configuration files

3. Optional – Machine Learning Concepts

011 About this section – intro to ML

012 What is an Artificial Neuron – Neural Network

013 Parts of an Artificial Neural Network

014 Explanation – Convolutional Neural Network

015 Recurrent Neural Networks basics RNNs

4. iOS Machine Learning With Photos

016 About this section – coreML with Photos

017 Demo of project using coreML on photos

018 About ML model and Neural Networks

019 Project_ Create the xcode project

020 Project_ How to add ML models to xcode projects

021 Project_ How to get pre-made ML models for iOS

022 Project_ How to use ML models with images (part 1)

023 Project_ How to use ML models with images (part 2)

024 Project_ Programming the VN request callback method

025 Testing different ML models

026 Exercise_ Models with Images input

027 Solution_ Models with Images input

028 Summary_ coreML Vision with Photos

5. coreML All about custom models

029 About this section – model conversion

030 Project_ Finding custom ML models

031 Project_ Converting ML models get Anaconda IDE

032 Installing Python libraries for core ML

033 Installing Caffe tools for core ML conversion

034 Project_ Converting scikit model to core ml mlmodel format

6. CoreML with Data Set models

035 Introduction to Working with Data sets

036 Project_ Create xcode project and add iris model

037 Project_ ML dataset project User Interface

038 Project_ Properties and picker delegate methods

039 Project_ Pickerview data source methods

040 Project_ Coding prediction for data sets

041 Project_ Code improvements

042 Important data set models information

7. Project: coreML with Video Camera

043 About CoreML with Video Camera

044 Project_ Create xcode project and add VGG16 model

045 Project_ Building the user interface

046 Project_ Video Stream variables setup

047 Project_ Program camera feed

048 Project_ Capture image from video stream for ML model

049 Project_ Programming the ML prediction launch

050 Project_ Processing the ML model output

050 Project_ Processing the ML model output

051 Testing the live camera feed with VGG model

8. END: iOS coreML fundamentals

052 Congratulations

9. Optional – Going the extra mile

053 Adding converted model metadata

054 Get a PixelBuffer from a UIImage

055 UIImage PixelBuffer extension (part 1)

056 UIImage PixelBuffer extension (part 2)

057 coreML prediction using UIImage PixelBuffer

10. Optional – Numerous Model Conversions

059 Caffe – Get a Caffe ML model with weights and labels

060 CoreML tools conversion code with Caffe

061 Exporting Caffe model to mlmodel format

062 Caffe – Using the Caffe model with iOS

063 Keras – Load Save Keras models and convert to mlmodel

064 Vision Image Request parameter options

11. Advanced Vision Techniques: Face Detection

065 Introduction to advanced ML with Vision

066 Project_ Create the user interface in storyboard