Welcome back.
Congratulations for getting the learned relationship.
So our model is being well trained.
Now let's plot the results.
Let's display the results in a graph.
Let me start with plt dot figure.
I'm creating a figure with ten inches and height six inches.
Dot scatter.
We need to pass four parameters the x and y.
Alpha is 70% transparency and label actual data and the plot.
Let me start plotting the X which is the predictions in red dots.
So as we learned before in the previous videos about the Matplot library, it's very important library
used to make the plotting and display and and display the results and visualizations.
Okay, then plot X label we have on x axis, we need to display the size of the houses in in square
feet and the y axis price in thousands of thousand dollars.
The title of this graph is House Price Prediction using TensorFlow legend.
Go and display a legend for the graph.
Also display a grid and show the plot run.
And here you will get this, uh, abnormal, uh, data.
Because those are not the real data.
They are scattered.
Okay, so, uh, to solve this, we need to run the program again and run all the cells from the beginning,
because, uh, maybe, maybe Google Colab, disconnect and reconnect.
So this connection will remove the model or maybe scatter that data, maybe diffuse the x and y.
So let's run from the beginning and make sure that everything will work fine.
And here we go.
We get another diagram.
Here we have the actual data displayed in uh in a correct way.
Also we have this red line the predicted a TensorFlow prediction.
So the red dots the red line represent the TensorFlow prediction while the blue ones represent the actual
data.
So congratulations guys for getting this data and displaying the results in this chart.