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Apple Has Launched the Latest Version of the Machine Learning Model Framework Core Ml 3 for IOS Deve
Apple Has Launched the Latest Version of the Machine Learning Model Framework Core Ml 3 for IOS Deve
At this year's world Developers Conference (WWDC), Apple launched the latest version of the machine learning model framework core ml 3 for IOS developers, introducing machine intelligence into smartphone apps. This article takes you through the highlights of core ml 3.Core ml 3 will be able to provide training for on device machine learning for the first time to provide a personalized experience of IOS app. The ability to train multiple models using different data sets will also become part of the new create ml app on MacOS for target detection and voice recognition.Support more than 100 model layersAs a way of rapid deployment and respecting privacy, machine learning on devices is becoming more and more popular. In recent months, popular frameworks such as tensorflow of Google and pytorch of Facebook have provided online machine learning solutions through methods such as federated learning.The core ml framework is used inside apple to train Siri, quicktype keyboard, language learning of memrise app and prediction of polar photo editing app.At last year's WWDC, Apple launched the core ML2 framework, claiming to be 30% faster than the previous generation, and launched create ml, a GPU accelerated framework for training customized AI models through Xcode and swift programming languages.The original ioscore ml framework was launched on WWDC in 2017 and incorporated into IOS 11. The preset model includes Apple's vision API and natural language framework.Unlike Google's ml kit, which is suitable for Android and IOS developers at the same time, coreml is designed for app developers who develop Apple's IOS operating system. At the end of 2017, Google announced that tensorflowlite supported coreml.Core ml 3 highlights firstWithout machine learning expertise, use core ml 3 and the new create ml app to easily create, train and deploy machine learning models.Core ml 3 integrates a variety of machine learning models into your app, supports advanced neural networks, supports more than 100 layers, and uses CPU, GPU and neural engine to provide the highest performance and efficiency. You can run the machine learning model directly on the device.Device model personalizationThe core ML model is bundled into the app to help drive intelligent functions such as searching in photos or object recognition. Now, these models can be updated through the user data on the device to help the model understand user behavior without violating privacy.Support advanced neural networksNow the most complex machine learning models can run on devices with core ml 3. You can use and run the latest models, such as cutting-edge neural networks for understanding images, video, sound and other rich media.visionEasily build computer vision machine learning function in app. Face detection, tracking and capture, text recognition, image saliency and classification, and image similarity recognition are used. Other functions include improved landmark detection, rectangle detection, bar code detection, target tracking and image registration. Use the new document camera API to detect and capture documents through the camera.natural languageThis paper analyzes the natural language text and deduces its language specific metadata for in-depth understanding. You can use this framework and create ml to train and deploy custom NLP models. Functions include transfer learning of create ml text model, word embedding, emotion classification and text directory. It can be used in English, French, German, Italian, simplified Chinese and Spanish.speechUse the speech recognition and speech saliency functions of 10 languages on the device, such as speech information, streaming confidence, speech detection and acoustic functions. Your app can disambiguate homonyms by accessing speech recognition information. These features are now also available for macapp.
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