October 2018
Intermediate to advanced
472 pages
10h 57m
English
Content preview from Python Deep Learning Projects
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Summary
In this implementation, we used a pretrained Inception-v3 model as a feature extractor in an encoder trained on the ImageNet dataset as part of a deep learning solution. This solution combines current state-of-the-art techniques in both computer vision and natural language processing, to form a complete image description approach (https://www.cs.cmu.edu/~afarhadi/papers/sentence.pdf) able to construct computer-generated natural descriptions of any provided images. We've effectively broken the barrier between images and language with this trained model and we've provided a technology that could be used as part of an application, helping the visually impaired enjoy the benefits of the megatrend of photo sharing! Great work!
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.