July 2018
Intermediate to advanced
474 pages
13h 37m
English
book
Apache Spark Deep Learning Cookbook
by Ahmed Sherif, Amrith Ravindra, Michal Malohlava, Adnan Masood
Content preview from Apache Spark Deep Learning Cookbook
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Consider the following:
- In our case, we notice the build_vocab function identifies 23,960 different word types from a list of 1,110,288 words. However, this number will vary for different text corpora.
- Each word is represented by a 300-dimensional vector since we have declared the dimensionality to be 300. Increasing this number increases the training time of the model but also makes sure the model generalizes easily to new data.
- The downsampling rate of 1e
3 is found to be a good rate. This is specified to let the model know when to downsample frequently occurring words, as they are not of much importance when it comes to analysis. ...
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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.