In this video, we’ll be building on what we’ve learned about MobileNet and the techniques we’ve used for fine-tuning to fine-tune MobileNet on a custom image data set that does not have classes similar to the ImageNet classes it was originally trained on.
We saw in the last video how well our fine-tuned MobileNet model performed on classifying images of cats and dogs. We noted, however, that many types of cat and dog breeds were included in the ImageNet data set that MobileNet was originally trained on, so we didn’t have to do too much tuning for our model to perform well on classifying the images.
Now, we’re going to see what we need to do to fine-tune MobileNet on a completely new type of data set, which doesn’t contain classes similar to those included in ImageNet. This data set is images of sign language digits. There are ten classes, labeled as zero through nine, and each class is made up of images of hands showing the sign for that particular digit.
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Sign Language Digits data set:
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Recommended books on AI:
The Most Human Human: What Artificial Intelligence Teaches Us About Being Alive:
Life 3.0: Being Human in the Age of Artificial Intelligence
Data Science – https://www.youtube.com/playlist?list=PLZbbT5o_s2xrth-Cqs_R9-us6IWk9x27z
Machine Learning – https://www.youtube.com/playlist?list=PLZbbT5o_s2xq7LwI2y8_QtvuXZedL6tQU
Keras – https://www.youtube.com/playlist?list=PLZbbT5o_s2xrwRnXk_yCPtnqqo4_u2YGL
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Investigations by Kevin MacLeod
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