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Cat/Dog/Human Image Recognition: Supervised Machine Deep Learning

Use artificial intelligence to identify an image of a cat, dog or human/person.

Supervised learning is a machine learning paradigm for problems where the available data consists of labeled examples, meaning that each data point contains features (covariates) and an associated label. The goal of supervised learning algorithms is learning a function that maps feature vectors (inputs) to labels (output), based on example input-output pairs.

See the code behind this.

Upload an image of a cat, dog or person and see if the computer can correctly categorize it.

The confusion matrix for this model. Trained to about 85%, some cats appear as dogs, some dogs appear as cats, and yes, some people appear as both...


cat
-24		dog
+17		human
+7
cat
625
511
80
34
dog
613
67
513
33
human
637
23
37
577
predicted category
true category
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