CoreML: Your Gateway to Machine Learning Applications in iOS

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CoreML: Your Gateway to Machine Learning Applications in iOS

Posted on By
Vishal Virani

Imagine a scenario when a friend of yours just went on a holiday and posted a few pictures. You want to know where they have been but, you cannot ask. Now, who will feed your knowledge? A mobile app will do it for you. There are apps with intelligence and knowledge fed into them, which help recognize pictures, places, people and other textual and image-based data. This kind of intelligence demonstrated by the apps is via the machine learning-induced into them.

With machine language, the industries can score better in terms of intelligence and their offering. Education technology can prepare lessons that are more immersive and help the children understand the concepts better. When machine learning is integrated with Augmented Reality or Virtual Reality, they intend to improve the experience of the user. The machine learning application will improve the speed of barcode tracking, facial recognition and other app abilities, one notch better.

CoreML for iOS

 

CoreML was introduced during Apple’s last year’s event and was proof enough of acceptance of ML in the world of mobile app development. Gradually, mobile apps are moving towards improving intelligence and growing to be more tactful for the users. CoreML will help developers add this intelligence quickly, without any issue.

Developers can even integrate their own machine learning models with this framework or use the pre-defined models for quicker access to the intelligence.

CoreML extends supports towards the different machine learning models that include tree ensembles, vector machines and neural networks. If your model has been defined using a format other than. mlmodelformat, then you will simply need to convert it to the said format and start using it.

Opportunities with Core ML

 

What you can achieve by integrating machine learning into your application is endless. In fact, one of the core transformations brought in by machine learning would be the face recognition ability depicted by the phones and apps. Unlocking your phone by feeding it with your image has become quite common. Machine learning is heavily responsible for this ability. Let’s look at how else facial recognition helps.

Recognition Technology:

 

Ever seen Facebook asking you to tag people with their names by the side? This is a form of machine learning for iOS that has been induced into the app, which makes the application recognize people easily. By integrating CoreML into your iOS app along with vision, you will be able to introduce features such as object recognition, facial recognition, barcode detection, object tracking etc. Accordingly, you will be able to introduce features into your app that the users are looking for. Tracking the products and their exact date of arrival is known via this technology. This opportunity would be extremely suitable to the ecommerce platforms

NLPs:


This is another aspect of machine learning app that can be used by the developers. With machine learning, you can allow apps to recognize speech, text and context. This will help apps with quicker replies and easier acknowledgment. One way of using it would be as replies to the emails or chats we send on a regular basis. There are both ready-to-use models as well as custom models that you can use to incorporate ML

Gameplay Kit:

 

This is well the third inclusion in the CoreML kit that you can utilize to improve the machine’s intelligence ability. Generating random numbers, organizing the game logic and building a game plan is made easy with this kit. In fact, if you are playing games that include pathfinding, agent tracking, artificial intelligence etc., then you ought to use this kit to deploy the best practice solution. The kit proves to be useful for the developers right from designing the application to strategizing it further and scaling it to new levels.

More about CoreML

 

You will need to work with Python if you want to setup the CoreML in your app. You will also need OS Sierra 10.12 and above to work with this framework. There is a complete documentation that will help you understand how to work around CoreML and how to use it to your advantage.

Xcode9 is your default software, which will help you work around apps with CoreML and iOS. You will need to log in coreml with your Apple ID, insert a six digit code before you can get started with Xcode9 for your app development.

Working with CoreML, means you are working with a single format. If the machine learning models you are trying to incorporate have a different format, then you might want to change the model before you use it in the app.

There is a simulator software that will help you understand how the machine learning model will be applicable in your application, and how it will appear once integrated. You might need to use it for better model integration.

Conclusion

 

Machine learning, as a concept is gaining importance, and you might want to use it to your advantage. With CoreML as part of your iOS development, you are in for a more secure and safe model working towards improving your machine’s learning ability and intelligence quotient.

Coruscate is an iOS app development company that offers simple and intuitive solutions to your app’s core learning ability. If you are looking for iOS machine learning apps, connect with us.

 

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