Welcome back.
I want from you to focus with me because in this video, we're gonna introduce something new.
We're going to connect our TensorFlow model with our Android application here.
Inside this app package, create a new others TensorFlow Lite model model location, search for model
location and select create ML directory in main and automatically add build feature and dependencies
to Build.gradle.
We added TensorFlow dependency, but Android will add other libraries like support and metadata and
also will add ML model binding.
True.
Automatically add TensorFlow Lite GPU dependencies to build greater.
This is optional, but I don't prefer to use it with emulators.
So click finish and here we go.
Wait, Gradle project sync to finish.
And you notice that ML package is created.
And inside it we have our model house price model TF Lite.
If you open it you can get this page.
Okay.
So this is how we add TensorFlow to our application and how we add TensorFlow model to the ML package.
Go to Build.gradle file.
And here we have TensorFlow support and metadata being added.
And you see in the build features we have ML model binding equals to true being added.
So in this way we added successfully the TensorFlow model to the Android Studio application.