January 2017
Beginner to intermediate
446 pages
8h 46m
English
Content preview from Artificial Intelligence with PythonBecome an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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Extracting the frequency of terms using a Bag of Words model
One of the main goals of text analysis is to convert text into numeric form so that we can use machine learning on it. Let's consider text documents that contain many millions of words. In order to analyze these documents, we need to extract the text and convert it into a form of numeric representation.
Machine learning algorithms need numeric data to work with so that they can analyze the data and extract meaningful information. This is where the Bag of Words model comes into picture. This model extracts a vocabulary from all the words in the documents and builds a model using a document term matrix. This allows us to represent every document as a bag of words. We just keep track of ...
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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.