Artificial Intelligence
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Image of little girl

is %s' % for_score) plt.imshow(image) if for_score >= 0.5: text = 'is' else: text = 'is not' plt.title('This model %s predict the presence of a little girl in the original photo with a certainty of %f percent' % (text, for_score*100)) model_evaluation('little girl', image, best_model, preprocessing='cnn') """ The performance of the 'cnn' model is significantly better for both visualizing the embedding input across the training epoch as well as when applied to the roughly similar but different image of a little girl. Given the built-in low dimension model compressing the large feature set while maintaining data fidelity, this model should prove useful in other applications such as music and other audio file classification, facial recognition and object or subject detection in other images, and various natural language processing tasks. The model will struggle in distinguishing object categories not well represented in the training set, so further refinements and increased training time may be necessary. That will be explored in future models. """