WEBVTT

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Welcome back.

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Congratulations for getting the learned relationship.

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So our model is being well trained.

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Now let's plot the results.

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Let's display the results in a graph.

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Let me start with plt dot figure.

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I'm creating a figure with ten inches and height six inches.

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Dot scatter.

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We need to pass four parameters the x and y.

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Alpha is 70% transparency and label actual data and the plot.

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Let me start plotting the X which is the predictions in red dots.

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So as we learned before in the previous videos about the Matplot library, it's very important library

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used to make the plotting and display and and display the results and visualizations.

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Okay, then plot X label we have on x axis, we need to display the size of the houses in in square

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feet and the y axis price in thousands of thousand dollars.

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The title of this graph is House Price Prediction using TensorFlow legend.

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Go and display a legend for the graph.

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Also display a grid and show the plot run.

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And here you will get this, uh, abnormal, uh, data.

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Because those are not the real data.

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They are scattered.

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Okay, so, uh, to solve this, we need to run the program again and run all the cells from the beginning,

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because, uh, maybe, maybe Google Colab, disconnect and reconnect.

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So this connection will remove the model or maybe scatter that data, maybe diffuse the x and y.

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So let's run from the beginning and make sure that everything will work fine.

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And here we go.

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We get another diagram.

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Here we have the actual data displayed in uh in a correct way.

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Also we have this red line the predicted a TensorFlow prediction.

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So the red dots the red line represent the TensorFlow prediction while the blue ones represent the actual

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data.

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So congratulations guys for getting this data and displaying the results in this chart.