Complete iOS 11 Machine Learning Masterclass | Simpliv

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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:

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<li>Master the 3 fundamental branches of applied Machine Learning: Image &amp; Video Processing, Text Analysis, and Speech &amp; Language Recognition</li>

<li>Develop an intuitive sense for using Machine Learning in your iOS apps</li>

<li>Create 7 projects from scratch in practical code-along tutorials</li>

<li>Find pre-trained ML models and make them ready to use in your iOS apps</li>

<li>Create your own custom models</li>

<li>Add Image Recognition capability to your apps</li>

<li>Integrate Live Video Camera Stream Object Recognition to your apps</li>

<li>Add Siri Voice speaking feature to your apps</li>

<li>Dive deep into key frameworks such as coreML, Vision, CoreGraphics, and GamePlayKit.</li>

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

<li>Get FREE unlimited hosting for one year</li>

<li>And more!</li>

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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 11 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 11 swift 4 coreml vision deep learning machine learning neural networks python anaconda trained models keras tensorflow scikit learn core ml ios11 Swift4 scikitlearn artificial neural network ANN recurrent neural network RNN convolutional neural network CNN ocr character recognition face detection ios 11 swift 4 coreml vision deep learning machine learning neural networks python anaconda trained models keras tensorflow scikit learn core ml ios11 Swift4 scikitlearn artificial neural network ANN recurrent neural network RNN convolutional neural network CNN ocr character recognition face detection ios 11 swift 4 coreml vision deep learning machine learning neural networks python anaconda trained models keras tensorflow scikit learn core ml ios11 Swift4 scikitlearn artificial neural network ANN recurrent neural network RNN convolutional neural network CNN ocr character recognition face detection ios 11 swift 4 coreml vision deep learning machine learning neural networks python anaconda trained models keras tensorflow scikit learn core ml ios11 Swift4 scikitlearn artificial neural network ANN recurrent neural network RNN convolutional neural network CNN ocr character recognition face detection ios 11 swift 4 coreml vision deep learning machine learning neural networks python anaconda trained models keras tensorflow scikit learn core ml ios11 Swift4 scikitlearn artificial neural network ANN recurrent neural network RNN convolutional neural network CNN ocr character recognition face detection

Who is the target audience?

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<li>People with a basic foundation in iOS programming who would like to discover Machine Learning, a branch of Artificial Intelligence</li>

<li>People who want to pursue a career combining app development and Machine Learning to become a hybrid iOS developer and ML expert</li>

<li>Developers who would like to apply their Machine Learning skills by creating practical mobile apps</li>

<li>Entrepreneurs who want to leverage the exponential technology of Machine Learning to create added value to their business could also take this course. However, this course does assume that you are familiar with basic programming concepts such as object oriented programming, variables, methods, classes, and conditional statements</li>

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<li>Basic understanding of programming</li>

<li>Have access to a MAC computer or MACinCloud website</li>

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<li>Build smart iOS 11 &amp; Swift 4 apps using Machine Learning</li>

<li>Use trained ML models in your apps</li>

<li>Convert ML models to iOS ready models</li>

<li>Create your own ML models</li>

<li>Apply Object Prediction on pictures, videos, speech and text</li>

<li>Discover when and how to apply a smart sense to your apps</li>

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