Over the past few years, researchers have been working on creating of machines, software, and applications that can make decisions without any human input. With machine learning and artificial intelligence, these innovations are being actualized. Different fields in various industries are now using machine learning.
The mobile application development field has not been left behind, either. We now have several ways in which machine learning can be applied in Android apps. The choice of the manner in which machine learning will be applied depends on the tasks you want to execute with the help of machine learning.
Machine learning is becoming more popular day in and day out. Perhaps this is because it contains algorithms that analyze the targeted user behavior patterns and make decisions or suggestions based on the patterns. A field that has widely adopted machine learning is mobile e-commerce. So how can machine learning be applied to Android?
Machine learning for Android apps
With the help of machine learning, you can make innovative transformations in whatever technological field you are operating on. That is why mobile app developers are actively using machine learning to create applications with smooth user interfaces. Some of these applications are empowering businesses because of the excellent features they have that can pinpoint the exact customer location.
Businesses can now create Android mobile applications to enable them run their operations smoothly. You can have the applications customized in any manner you want. You can contact ActiveWizards machine learning engineers to help you create these apps. Some of the popular mobile apps that use machine learning include Netflix, Tinder, and Google Maps.
Making a machine learning Android app
Designing machine learning applications is no easy feat. Just a basic understanding in machine learning is not enough. You must have a great understanding of both neural networks and data analysis. The understanding will enable you to get started with the machine learning frameworks like TensorFlow and CloudVision.
The entire process is a complex one because you have to collect, clean, and filter that data and then feed your results while properly utilizing ML frameworks to reach at the required objective.
Getting started using TensorFlow
TensorFlow is a Google open source library that is used to implement machine learning in Android. TensorFlow Lite is the most widely-used framework in mobile devices. The framework is preferred for android because it is small in size and supports hardware acceleration using Android neural networks API.
When using TensorFlow Lite, the model has to be changed to (.tflite). You will then use this model to begin Android application development and then predict the output using the TensorFlow Lite library.
Training a TensorFlow model on Android
Training a TensorFlow model on Android can be time consuming as it requires a huge quantity of data. Transfer learning has been widely used to shorten the training time where a previously trained model is used to create a new one. All you have to do is gather the training data, change the data into the required images, group them, and then retrain the model with new images. You will then locally test the app for any defects.