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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 to do it…

In the following steps, we will read in a dataset of passwords, along with labels for their strength, and build a classifier to assess password strength. Let's get started:

  1. Import pandas and read in the passwords into a dataframe:
import pandas as pddf = pd.read_csv(    "passwordDataset.csv", dtype={"password": "str", "strength": "int"}, index_col=None)
  1. Shuffle the data at random:
df = df.sample(frac=1)
  1. Split the dataframe into two separate dataframes, one for training and one for testing:
l = len(df.index)train_df = df.head(int(l * 0.8))test_df = df.tail(int(l * 0.2))
  1. Create the required labels and featured data:
y_train = train_df.pop("strength").valuesy_test = test_df.pop("strength").valuesX_train = train_df.values.flatten() ...
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Publisher Resources

ISBN: 9781789614671Supplemental Content