What is Google ML Kit and How it works? An Overview and Its Use Cases

ML Kit is Google’s machine learning expertise for mobile developers in one powerful and easy-to-use package. Make your iOS and Android apps more attractive, personalized and helpful with solutions optimized to run on all devices.ML Kit is a mobile SDK that brings Google’s on-device machine learning expertise to Android and iOS apps. Use our powerful yet easy to use Vision and Natural Language APIs to solve common challenges in your apps or create brand-new user experiences.ML is not available in stable version ML Kit is still only available in beta version. It can be launched using Firebase.ML Kit gives you both on-device and Cloud APIs, all in a common and simple interface, allowing you to choose the ones that fit your requirements best

Following are the features:

• Text recognition
• Face detection
• Barcode scanning
• Image labeling
• Object detection & tracking
• Landmark recognition
• Language identification
• Translation
• Smart reply
• Auto ML model inference
• Custom model inference.

How does it work?

ML Kit is Google’s machine learning expertise for mobile developers in one powerful and easy-to-use package.ML Kit makes it easy to implement ML technologies in your apps by bringing together Google’s ML technologies, such as the Google Cloud Vision API, TensorFlow Lite, and the Android Neural Network API, into one 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 a few lines of code.

Why should use ML kit

Machine Learning (ML) is the field of computational science. Machine learning is important because it gives enterprises a view of trends in customer behavior and business operational patterns, as well as supports the development of new products. Many of today’s leading companies, such as Facebook, Google and Uber, make machine learning a central part of their operations. Machine learning has become a significant competitive differentiator for many companies.

Alternative of ML kit

• Scikit-learn
• Keras
• G2 Deals
• Keysight Eggplant Platform
• machine-learning in Python
• V7
• Personalizer
• TFlearn
• NVIDIA Deep Learning GPU Training System (DIGITS)
• Kubernetes
• Google Cloud TPU

Interview Question and Answer of Google ML

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