October 2018
Intermediate to advanced
472 pages
10h 57m
English
Content preview from Python Deep Learning Projects
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Summary
We dove right into this deep-learning project in Python, creating and training an ASR model that understands speech data. We learned to feature engineer the speech data to extract various kinds of features from it and then build a speech recognition system that could detect a user's voice.
We're happy to have achieved our stated goal!
In this chapter, we built a system that recognizes English speech, using the DS2 model.
You learned following:
- To work with speech and spectrograms
- To build an end-to-end speech recognition system
- The CTC loss function
- Batch normalization and SortaGrad for RNNs
This caps off a major section of the deep-learning projects in this Python book that explores chatbots, NLP, and speech recognition with RNNs ...
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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.