iOS Machine Learning with Core ML 2 and Swift 5

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Karoly Nyisztor • Professional Software Architect

2:08:32

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1 - Introduction

1 - Test Your Skills.html

1 - What is Machine Learning.mp4

03:14

2 - What You Should Know.mp4

01:21

3 - Join the Official Student Group.html

4 - Supervised and Unsupervised Machine Learning.mp4

02:00

5 - The Machine Learning Model.mp4

02:43

6 - iOS and Machine Learning.mp4

01:05

7 - Exercise Files.mp4

01:00

2 - iOS Machine Learning Architecture

8 - A High.mp4

01:15

9 - The CoreML Framework.mp4

01:13

10 - The NaturalLanguage Framework.mp4

01:25

11 - The Vision Framework.mp4

01:47

12 - The GamePlayKit Framework.mp4

03:08

3 - Natural Language Text Analysis

13 - Natural Language Text Analysis What Are We Going to Build.mp4

01:23

14 - Recognizing the Dominant Language of a Text.mp4

06:06

15 - Tokenizing a String.mp4

04:13

16 - Identifying Parts of Speech.mp4

03:22

17 - Identifying People Places and Organizations.mp4

02:16

4 - Image Analysis with the Vision Framework

18 - Image Analysis with the Vision Framework What Are We Going to Build.mp4

00:52

19 - The Starter App.mp4

03:45

20 - Analyzing Still Images using Vision.mp4

01:30

21 - Implementing the Image Request Handler.mp4

07:05

22 - Implementing the Image Analysis Request.mp4

06:30

23 - Converting Coordinates Between Quartz 2D and UIKit.mp4

03:55

24 - Visualizing the Detected Rectangles.mp4

06:35

25 - Recognizing Text Faces and Barcodes in Still Images.mp4

04:25

5 - Training a Flower Classifier on Your Computer using Create ML

26 - Training a Flower Classifier on Your Computer What Are We Going to Build.mp4

00:42

27 - Recognizing Flowers.mp4

02:24

28 - Training an Image Classifier in a Playground.mp4

04:31

29 - Recognizing Flowers.mp4

02:02

30 - Integrating the Flower Classifier Model.mp4

04:00

31 - Displaying Predictions.mp4

03:00

32 - Picking an Image.mp4

02:37

33 - Performing the Image Analysis Request.mp4

03:00

34 - The Flower Recognizer App in Action.mp4

02:44

6 - Determining the Tonality of a Review

35 - Review Sentiment Analysis.mp4

00:36

36 - Preparing the Training Data for the Review Sentiment Classifier.mp4

01:23

37 - Training a Text Classifier in a Playground.mp4

06:03

38 - Creating the MLTextClassifier.mp4

05:16

39 - Saving the Core ML Model.mp4

02:57

40 - Laying Out the User Interface of the Review Classifier App.mp4

02:59

41 - Integrating the Review Classifier Model.mp4

06:42

42 - Testing the Review Classifier App.mp4

04:25

7 - Next Steps Bonuses

43 - Goodbye.mp4

01:03

44 - Companion eBook.html

44 - MachineLearningwithCoreML2andSwift.pdf

45 - Bonus Lecture Learn More from Karoly Useful Links.html

Description

Learn how to integrate machine learning into iOS apps. Hands-on Swift 5 coding using CoreML 2, Vision, NLP and CreateML.

What You'll Learn?

Learn from a software engineer with 20+ years of professional experience
Get a practical introduction to machine learning in the context of iOS and macOS development
Get the companion e-book for FREE! (sells for $28.80 on Amazon)
Learn how to integrate natural language text analysis into your apps
Build apps that can recognize and classify objects in images and video streams
Use Core ML to perform sentiment analysis on Amazon product reviews
Gain a working knowledge of Core ML 2, Vision, Natural Language Processing and Create ML

Who is this for?

Take this course if you want to get started with Core ML, Vision, and/or Natural Language Processing

This course is for you if you want to bring your game to the next level by integrating machine learning into your apps

What You Need to Know?

You need a Mac with macOS Mojave and Xcode 10 or later

You should have basic Swift programming skills

You should definitely go ahead if you know how Xcode works

More details

Description
A practical and concise Core ML 2 course you can complete in less than three hours. Companion eBook included!
Wouldn't it be great to integrate features like synthetic vision, natural language processing, or sentiment analysis into your apps? In this course, I'll teach you how to unleash the power of machine learning using Apple Core ML 2. I'll show you how to train and deploy models for natural language and visual recognition using Create ML.
I'm going to familiarize you with common machine learning tasks. We'll focus on practical applications, using hands-on Swift coding.
We're going to demystify what machine learning is by investigating how it works. And no worries, I introduce each concept using simple terms, avoiding confusing jargon.
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!
What qualifies me to teach you?
I have more than 25 years of software development expertise. I've worked for companies like Apple, Siemens, and SAP.
As a software architect, I have designed and built several enterprise systems and frameworks, including core components of Siemens Healthcare's syngo image processing system. I'm one of the senior software architects behind the SAP Cloud Platform SDK for iOS, a framework built by Apple and SAP. I currently hold twelve patents related to inventions in the field of mobile computing.
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 5" is the perfect course for you if you're interested in machine learning.

STUDENT REVIEWS
â€œThank you Karoly, you have delivered another excellent course, with detailed explanations and real world examples of machine learning that any app developer will be able to put into practice with their app development.Excellent course.â€ - Jim McMillan
â€œThis course is the best introduction to Machine Learning with Swift. It is going to familiarize you with common machine learning tasks and is very helpful for beginners.â€ - Zbyszek Pietras
â€œI've been looking for a course that teaches CoreML2 with natural language processing and CreateML. I found this course very useful and gets directly to the important topics. I also appreciated the Vision CoreML section as well.â€ - Dan Gray

MORE THAN AN ONLINE COURSE. WITH THIS CLASS, YOU ALSO RECEIVE:
Personalized support
As a student of this course, youâ€™ll get access to the course's private forum, where I answer questions and provide support if necessary.
The companion eBook
Downloadable resources
You get downloadable demo projects you can use to follow along.
Continuous updates
I keep enhancing this course to provide fresh and up-to-date content.

OUR 30-DAY MONEY-BACK GUARANTEE
If you aren't satisfied with your purchase, we'll refund you your money. We want to make sure you're completely satisfied with the course. That's why we're happy to offer you this money-back guarantee.
Go ahead and click the enroll button. See you in the first lesson!
Who this course is for:
Take this course if you want to get started with Core ML, Vision, and/or Natural Language Processing
This course is for you if you want to bring your game to the next level by integrating machine learning into your apps

User Reviews

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Károly Nyisztor is a professional software engineer, instructor, and author. So far, he has inspired over 150,000 students worldwide. As an instructor, he aims to share his more than 25 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.Karoly has worked for companies like Apple, Siemens, and SAP. As a software architect, he has designed and built several enterprise frameworks. He currently holds twelve patents related to inventions in the field of mobile computing.He has worked with various technologies and programming languages, including x86 Assembly, C, C++, Java, Objective-C, Swift, and Python. Karoly has built several successful iOS apps and games that Apple has featured as ”New and Noteworthy,” ”App of the Month,” and “Best Travel Apps.”After 18 years, he left the corporate world to start his own business. He is the founder of LEAKKA, a software development and tech consulting company. Since 2016, he has been fully committed to teaching.Karoly teaches Software Architecture, Object-Oriented Programming and Design, Software Security, iOS Programming, Machine Learning, Swift and Python Programming, and UML.

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