August 2017
Beginner to intermediate
340 pages
8h 42m
English
Content preview from Mastering Machine Learning with Spark 2.x
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What is a word vector?
In its simplest form, a word vector is merely a one-hot-encoding, whereby every element in the vector represents a word in our vocabulary, and the given word is encoded with 1 while all the other words elements are encoded with 0. Suppose our vocabulary only has the following movie terms: Popcorn, Candy, Soda, Tickets, and Blockbuster.
Following the logic we just explained, we could encode the term Tickets as follows:
Using this simplistic form of encoding, which is what we do when we create a bag-of-words matrix, there is no meaningful comparison we can make between words (for example, is Popcorn related to Soda; is ...
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