Precision and recall
How good is your model? Watch the video on this step which explains the principles behin evaluating your model.
At this point in the course, you have successfully built your first model to classify portrait and landscape paintings based on their physical dimensions.
Now we must ask ourselves how good will it be in predicting the right answer? In other words, how accurately does it predict the right label, does it correctly identify only the relevant items of data, and has it classified all instances of the data we wish to find?
Your task
Watch the video and learn the principles behind how we will evaluate our model.In the comments, explore how the example of receiving signals in a radar system relates to our example of classifying portrait and landscape paintings.
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