Hello developers, and welcome back.
In this section we're going to build an amazing application called House Price Prediction Application.
We're going to mix and integrate machine learning with Android.
We'll train a simple model with TensorFlow from scratch to learn the equation and correlation between
the size of house and its price.
So we're going to start with installing TensorFlow, then generating random data, then reshaping data,
building TensorFlow model, training the model, get the trained weights and bias plotting the results.
So we're going to see the coloration and the actual data and the TensorFlow prediction.
We're going to evaluate the model by plotting the errors and see the model loss.
Also we're going to save and export the model.
How to export our model in TensorFlow format.
Also we're going to learn how to load models, how to load the exported models.
Also, the most important thing we're going to learn is exporting models as TF Lite for Android TF Lite
format optimized for mobile and edge devices like microcontrollers.
So we're going to export our model and use it in Android Studio.
So through this amazing tutorial we're going to build this application.
So this application let me show you what it does I gave the model the TensorFlow model 100 data 100
sizes of the the the houses and their prices.
It predicted the price of any any house you gave us as a size.
So give me the size.
I'll give you the price.
This is the TensorFlow job okay.
So here I'll give it a house size in thousands of square feet.
So 1.5 means 1500ft².
And let me predict this.
So here click on predict house price.
And the price of the house is 6.548.
The model learned the relationship when when we we give when we gave the model 100 data 100 size and
the price.
There is an equation learned by the model.
And this learned equation is used to predict the price of the house.
For example, 1.5 if we go to here to the, uh, the house prediction using TensorFlow, this graph
1.5, it's approximately 6.5 okay.
So if we make a prediction so it's approximately is 6.5.
So it predicted right numbers.
Okay.
So we're going to make sure that our model is well trained and everything is working fine.
Let me try another prediction example.
So predict house price and with 2000ft² house, its price would be $8,000.
If we make a projection here we see that it is.
It's close to $8.05 thousand.
Okay.
So congratulations guys for reaching this section.
Also, this is a big section.
And um, I want from you to understand everything I want from you to follow me.
There are a lot a lot of notes I want from you to write them down, because they help you to memorize
and understand what we're going to build.
Guys, this is a very important section.
This is the building block of your machine learning and Android integration career.