Google's ML-Kit for Mobile Development || Univ_Techs



     ML Kit is a mobile SDK that brings Google's machine learning expertise to Android and iOS apps in a powerful yet easy-to-use package. Whether you're new or experienced in machine learning, you can implement the functionality you need in just a few lines of code. There's no need to have deep knowledge of neural networks or model optimization to get started. On the other hand, if you are an experienced ML developer, ML Kit provides convenient APIs that help you use your custom TensorFlow Lite models in your mobile apps.



     At Google I/O'18 developer conference in May, Google introduced ML Kit, a cross-platform suite of machine learning tools for the Firebase mobile development platform. ML Kit uses the Neural Network API on Android devices and is designed to compress and optimize machine learning models for mobile devices.  It brings Google’s machine learning expertise to mobile developers in a powerful and easy-to-use package.

ML Kit makes it easy to apply ML techniques in your apps by bringing Google's ML technologies, such as the Google Cloud Vision API, TensorFlow Lite, and the Android Neural Networks API together in a single SDK. Whether you need the power of cloud-based processing, the real-time capabilities of mobile-optimized on-device models, or the flexibility of custom TensorFlow Lite models, ML Kit makes it possible with just a few lines of code.

It Offers both by Google Cloud Platform’s and API's. Google says that new APIs, including a smart reply API that supports in-app contextual messaging replies and an enhanced face detection API with high-density face contours, will arrive in late 2018.

ML Kit’s base APIs cover:
  • Barcode scanning, to scan and process barcodes.
  • Text recognition.
  • Face detection.
  • Landmark detection, to identify popular landmarks.
  • Image labeling, to identify objects, locations, activities, products, and animal species.
     You can use Google's ML Kit through this link on Firebase.

     Finally, ML Kit works with Firebase features like A/B testing, which lets users test different machine learning models dynamically, and Cloud Firestore, which stores image labels and other data.

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