This is an example project for integrating TensorFlow Lite into Android application This project include an example for object detection for an image taken from camera using TensorFlow Lite library.

Project on Disease Prediction Using Machine Learning implemented as an Android app. - synthwrkx/Disease_Prediction_Android_App ...

With Firebase ML Kit, Google are aiming to make machine learning more accessible, by providing a range of pre-trained models that you can use in your iOS and Android apps. In this article, I’ll ...

Machine learning can help you create innovative, compelling and unique experiences for your mobile users - but if you want to enhance your Android apps with powerful machine learning capabilities ...

Java users can integrate ML into their Spring applications with Spring Boot Starter for Deep Java Library. Apply these frameworks to integrate ML capabilities into microservices for deep learning.

The pressure is on to harness machine learning for more responsive enterprise apps. So find the open source tool that works best for your programming style and architecture.

Artificial intelligence (AI) and machine learning (ML) are increasingly important in the world of enterprise development. That means programmers must learn the ins and outs of AI and ML. Five ML links ...

For a supervised machine learning project, you will need to label the data in a meaningful way for the outcome you are seeking. In Table 1, note that each row of the house record includes a label ...