January 2019
Intermediate to advanced
294 pages
6h 43m
English
Content preview from Machine Learning Quick Reference
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Bags of words
When we have text as input data, we can't go ahead and work with raw text. Hence, it's imperative for that text input data to get converted into numbers or vectors of numbers, in order to make it usable for a number of algorithms.
A bag of words model is one of the ways to make the text usable for the algorithms. Essentially, it is a representation of text that works on the occurrence of words in the document. It has nothing to do with the structure, order, and location; this model only looks for the count of the words as a feature.
The thought process behind this model is that having similar content means having a similar document.
The different steps to be taken in the bag of words model are as follows:
- Building the corpus ...
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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.