December 2019
Intermediate to advanced
468 pages
14h 28m
English
Content preview from Advanced Deep Learning with Python
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CBOW
CBOW predicts the most likely word given its context (surrounding words). For example, given the sequence The quick _____ fox jumps, the model will predict brown. The context is the n preceding and the n following words of the word in focus (unlike NPLM, where only the preceding words participate). The following screenshot shows the context window as it slides across the text:
A word2vec sliding context window with n = 2. The same type of context window applies to both CBOW and Skip-gram
CBOW takes all words within the context with equal weights and doesn't consider their order (hence the bag in the name). It is somewhat similar to NPLM, ...
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I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
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.