Android Machine Learning with Firebase ML Kit in Java/Kotlin


Android Machine Learning with Firebase ML Kit in Java/Kotlin

Firebase ML Kit for Android Developer's
Make your Android Applications smart, use ML trained model or train your own ML models explore the power of AI and Machine Learning.
This course was recorded using Android Studio 3.6.1 (which is a great introduction to the development environment!) For a smooth experience I'd recommend you use the same, but students can still use the latest Android Studio version available if they prefer!

Wish you’d thought of Object Recognition/Face Detection/Text Recognition?
Me too.
But until I work out how to build a time machine.
Here’s the next best thing.
Firebase ML Kit for Android Developer's
In this course, we will explore the features of Firebase ML Kit for Android. We will start by learning about Firebase ML Kit and Features it provides. Then we will see how to integrate ML Kit inside your Android Application just using Android studio. After that, we will explore the features of ML Kit and develop Android Applications like

  • Text Recognition Android Application
  • Android Application to Translate between Languages
  • Language Detection Application
  • Face Detection Application
  • Barcode Scanner Android Application
  • Object Detection Android App
  • Landmark Recognition Application
  • Stones Recognition Application
Then we will learn about Auto ML Vision edge feature of Firebase ML Kit using which we can train Machine Learning model on our own dataset and build Android Application for that model. We will train model to recognize different types of stones and build an Android App for that model.
At the end of this course, we will combine different features of Firebase ML kit to build an Android Application to categorize images of mobile gallery.

Who this course is for:
  • Beginner Android Developers want to make their applications smart
  • Android Developers want to use Machine Learning in their Android Applications
  • Developers interested in practical implementation of Machine Learning and computer vision

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