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Machine Learning for Cybersecurity Cookbook
book

Machine Learning for Cybersecurity Cookbook

by Emmanuel Tsukerman
November 2019
Intermediate to advanced content levelIntermediate to advanced
346 pages
9h 36m
English
Packt Publishing
Content preview from Machine Learning for Cybersecurity Cookbook

How it works...

We begin the recipe by importing the Markovify library, a library for Markov chain computations, and reading in text, which will inform our Markov model (step 1). In step 2, we create a Markov chain model using the text. The following is a relevant snippet from the text object's initialization code:

class Text(object):    reject_pat = re.compile(r"(^')|('$)|\s'|'\s|[\"(\(\)\[\])]")    def __init__(self, input_text, state_size=2, chain=None, parsed_sentences=None, retain_original=True, well_formed=True, reject_reg=''):        """        input_text: A string.        state_size: An integer, indicating the number of words in the model's state.        chain: A trained markovify.Chain instance for this text, if pre-processed. parsed_sentences: A list of lists, where ...
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Publisher Resources

ISBN: 9781789614671Supplemental Content