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Machine learning in IOS | raywenderlich.com



Core ML and Create ML-

Welcome to machine learning in IOS video courses! In this introduction you will find out what the course will cover.


Use Core ML with a model that has already been trained for you and learn about how models are handled by Xcode.


Apple's Vision framework was introduced with Core ML in iOS 11. They easily integrate for data vision tasks.


Analyze the results using a binary classifier. It will attempt to classify an image you show it, even if it results in nonsense!


Explore what happens when more than one object is in your image or your model can recognize more than two classes.


Using others' models is often not sufficient. Create ML will allow you to train your own! Here you use it on a playground.


Collecting good data is the key in ML. Listen to the cure process our team went through to provide the dataset for this course.


Repeat how you learned to work with ML models, no matter what budget you have for data collection and model training.


Turi Create

If you're going to be serious about Machine Learning, you have to be or become a Python tag! Turi Create has a Python API.


Get started with a Python-based machine learning environment based on Anaconda and Jupyter Notebook.


Despite the difference in programming language (Python vs Swift), Turi creates a lot with Create ML – including learning transfer.


Continue to train the snack classifier using Turi Create, to learn more about the API for model management.


Confusing matrices are a very useful visualization of how well your model performs. Learn how to use them in a Jupyter notebook.


Turi Create Public API provides limited control over the model training process, but it is open source and hides some taxes!


You have become familiar with machine learning in two popular environments. But, armed with your Python knowledge, it's still a great world of ML to explore!



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