Machine Learning in Apple Style:
Machine learning is something which every operating system wants to provide to their users. Like, always Apple took one step further and dreamt of launching user-friendly machine learning system. In WWDC 2017, the Apple main focus was on the machine learning and making it easier for the web developers to reach them. The mainly three machine learning systems of Apple are trending nowadays, Metal, a new computer vision framework, and Core ML: a toolkit that makes it really easy to put ML models into your app. Now in the article, we will take look brief at the machine learning experience with the iOS and how different it is from others.
This is the most talked feature of Apple’s machine learning and the simple features of it are very well preferred by the web developers. The API of Core ML is very simple and revolves around the main three functions. One can load trained models, making predictions and profit. Well, this seems to very fewer features, but one web developers here agree with me that how daunting task is to make one trained loaded model. Here Core ML offering this in very simple way.
The model is contained in a .mlmodel file. This is a new open file format that describes the layers in your model, the input and outputs, the class labels, and any preprocessing that needs to happen on the data. The everything is contained in the one open file which any one required to establish one file.
The next destination of the Apple machine learning train is vision framework. A vision framework is introduced in the iOS 11. Well, the vision allows users to perform computer vision related tasks. Before for the vision framework OpenCV is used by the phones, but now iOS has their own API to perform such operations. The functioning with the new vision framework is very simple and has numerous benefits.
The vision framework identifies the faces in the image and put them in the rectangular box. The advance vision framework can’t miss the single details of the facial features, like noise and eyes details can be easily seen through the vision framework. The every rectangular object can see and identify the road signs in the image with this power vision. Every bar code and technical saying can’t be missed. The joining to images is very productive task with this Apple vision framework.
The Metal Performance Shaders (MPS) is very popular and new iOS 11 has introduced some new features in it. As iOS 10 had few basic kernels for creating convolutional networks. Often it was necessary to write custom kernels to fill in the gaps. But in new iOS better and improved kennels are available. Now on the iOS, we have API for creating graphs. One can now create RNN, LSTM, GRU, and MGU layers. These work on sequences of MPSImage objects but also on sequences of MPSMatrix objects.
The Apple new API has numerous benefits but has some limitations also. Like, they are not open source, they have limitations and they’re only updated with new OS releases. But, still Apple APIs are very dynamic and the Apple team is working hard to improve its performance.