Complete iOS Machine Learning Masterclass

  • Overview
  • Curriculum
  • Instructor
  • Review

About This Course

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

If you want to learn how to start building professional, career-boosting mobile apps and use Machine Learning to take things to the next level, then this course is for you. The Complete iOS Machine Learning Masterclass™ is the only course that you need for machine learning on iOS. Machine Learning is a fast-growing field that is revolutionizing many industries with tech giants like Google and IBM taking the lead. In this course, you’ll use the most cutting-edge iOS Machine Learning technology stacks to add a layer of intelligence and polish to your mobile apps. We’re approaching a new era where only apps and games that are considered “smart” will survive. (Remember how Blockbuster went bankrupt when Netflix became a giant?) Jump the curve and adopt this innovative approach; the Complete iOS Machine Learning Masterclass™ will introduce Machine Learning in a way that’s both fun and engaging.

In this course, you will:

  • Master the 3 fundamental branches of applied Machine Learning: Image & Video Processing, Text Analysis, and Speech & Language Recognition

  • Develop an intuitive sense for using Machine Learning in your iOS apps

  • Create 7 projects from scratch in practical code-along tutorials

  • Find pre-trained ML models and make them ready to use in your iOS apps

  • Create your own custom models

  • Add Image Recognition capability to your apps

  • Integrate Live Video Camera Stream Object Recognition to your apps

  • Add Siri Voice speaking feature to your apps

  • Dive deep into key frameworks such as coreML, Vision, CoreGraphics, and GamePlayKit.

  • Use Python, Keras, Caffee, Tensorflow, sci-kit learn, libsvm, Anaconda, and Spyder–even if you have zero experience

  • Get FREE unlimited hosting for one year

  • And more!

This course is also full of practical use cases and real-world challenges that allow you to practice what you’re learning. Are you tired of courses based on boring, over-used examples?  Yes? Well then, you’re in a treat. We’ll tackle 5 real-world projects in this course so you can master topics such as image recognition, object recognition, and modifying existing trained ML models. You’ll also create an app that classifies flowers and another fun project inspired by Silicon Valley™ Jian Yang’s masterpiece: a Not-Hot Dog classifier app!

Why Machine Learning on iOS

One of the hottest growing fields in technology today, Machine Learning is an excellent skill to boost your your career prospects and expand your professional tool kit. Many of Silicon Valley’s hottest companies are working to make Machine Learning an essential part of our daily lives. Self-driving cars are just around the corner with millions of miles of successful training. IBM’s Watson can diagnose patients more effectively than highly-trained physicians. AlphaGo, Google DeepMind’s computer, can beat the world master of the game Go, a game where it was thought only human intuition could excel.

In 2017, Apple has made Machine Learning available in iOS so that anyone can build smart apps and games for iPhones, iPads, Apple Watches and Apple TVs. Nowadays, apps and games that do not have an ML layer will not be appealing to users. Whether you wish to change careers or create a second stream of income, Machine Learning is a highly lucrative skill that can give you an amazing sense of gratification when you can apply it to your mobile apps and games.

Why This Course Is Different

Machine Learning is very broad and complex; to navigate this maze, you need a clear and global vision of the field. Too many tutorials just bombard you with the theory, math, and coding. In this course, each section focuses on distinct use cases and real projects so that your learning experience is best structured for mastery.

This course brings my teaching experience and technical know-how to you. I’ve taught programming for over 10 years, and I’m also a veteran iOS developer with hands-on experience making top-ranked apps. For each project, we will write up the code line by line to create it from scratch. This way you can follow along and understand exactly what each line means and how to code comes together. Once you go through the hands-on coding exercises, you will see for yourself how much of a game-changing experience this course is.

As an educator, I also want you to succeed. I’ve put together a team of professionals to help you master the material. Whenever you ask a question, you will get a response from my team within 48 hours. No matter how complex your question, we will be there–because we feel a personal responsibility in being fully committed to our students.

By the end of the course, you will confidently understand the tools and techniques of Machine Learning for iOS on an instinctive level.

Don’t be the one to get left behind.  Get started today and join millions of people taking part in the Machine Learning revolution.
































topics: ios swift 4 coreml vision deep learning machine learning neural networks python anaconda trained models keras tensorflow scikit learn core ml ios12 Swift4 scikitlearn artificial neural network ANN recurrent neural network RNN  convolutional neural network CNN ocr character recognition face detection  ios swift 4 coreml vision deep learning machine learning neural networks python anaconda trained models keras tensorflow scikit learn core ml ios12 Swift4 scikitlearn artificial neural network ANN recurrent neural network RNN  convolutional neural network CNN ocr character recognition face detection  ios swift 4 coreml vision deep learning machine learning neural networks python anaconda trained models keras tensorflow scikit learn core ml ios12 Swift4 scikitlearn artificial neural network ANN recurrent neural network RNN  convolutional neural network CNN ocr character recognition face detection  ios swift 4 coreml vision deep learning machine learning neural networks python anaconda trained models keras tensorflow scikit learn core ml ios12 Swift4 scikitlearn artificial neural network ANN recurrent neural network RNN  convolutional neural network CNN ocr character recognition face detection  ios  swift 4 coreml vision deep learning machine learning neural networks python anaconda trained models keras tensorflow scikit learn core ml ios12 Swift4 scikitlearn artificial neural network ANN recurrent neural network RNN  convolutional neural network CNN ocr character recognition face detection  

  • Build smart iOS 11 & Swift 4 apps using Machine Learning

  • Use trained ML models in your apps

  • Convert ML models to iOS ready models

Course Curriculum

1 Lectures

Instructor

Profile photo of Yohann Taieb
Yohann Taieb

Yohann holds a Bachelor of Science Degree in Computer Science from FIU University. He has been a College instructor for over 15 years, teaching iPhone Development, iOS 15, Apple Watch development, Swift 5, Unity 3D, Pixel Art, Photoshop for programmers,  Android and blockchain development. Yohann also has plenty of ideas which naturally turned him into an entrepreneur, where he owns...

Review
4.9 course rating
4K ratings
ui-avatar of Tariq Maged
Tariq M.
4.5
1 year ago

Good Course with useful information

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ui-avatar of Srinivas Varada
Srinivas V.
5.0
1 year ago

Amzing

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ui-avatar of Aly Davis
Aly D.
5.0
3 years ago

very clear so far, thanks!

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ui-avatar of Bruce
Bruce
3.0
3 years ago

I need swiftui + swift5

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ui-avatar of Mayur Shah
Mayur S.
3.0
4 years ago

Expecting more detail oriented.

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ui-avatar of Nicholas Allio
Nicholas A.
1.5
5 years ago

I was expecting the course covering more Ml rather than some iOS fundamentals: it spent the most of the time coding for setting up the UI and collect data from standard controller rather than dig into ML in details. The actual sections covering ML are very little respect of the rest.

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ui-avatar of Danny Silva
Danny S.
2.5
6 years ago

Interesting course, and clear on instructions.

Instructor takes long to reply. His core provided code for the main points of the course doesn't compile...

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ui-avatar of Alan Swithenbank
Alan S.
5.0
6 years ago

I took this course in its iOS 11 incarnation, and am looking forward to going back through for the iOS 12 updates. It's a fast paced course, so, you should have some iOS programming under your belt beforehand. I had a few sticky problems with some of the library installs that others didn't, but, that's computers, no two are alike, and not the fault of the course. The information provided is concise but complete, and the examples provide useful bases to build on.

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ui-avatar of James Foley
James F.
1.0
7 years ago

Too much talk, not enough code.

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ui-avatar of Lin Hiu Wai
Lin H. W.
5.0
7 years ago

Lecturer is really passion for making iOS App and is willing to share his knowledge for students.

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