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Installation and Setup

Importing Packages to Python 3

Let's get started by importing some packages we will need for this workshop.

import nltk
from nltk.corpus import brown
from nltk import pos_tag_sents
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline
import sklearn

Line-by-line, here is what we must import and why, in order to begin our machine learning process:

  • nltk, the Natural Language ToolKit, which will be used for corpora and tools:
    • brown: The Brown Corpus, a text corpus of American English, split into fifteen different categories.
    • pos_tag_sents Part of speech taggers (POS): prebuilt functions that are designed to determine the part of speech of every word in the sentence you give them.
  • pandas as pd: importing the Pandas toolkit, which we will be using for data processing. We are renaming it pd to make the command briefer for us to type each time we use it.
  • matplotlib.pyplot as plt: We will use MatPlotLib for visualizing our data. We are importing the plotting tools here, and renaming them plt.
  • sklearn: This is the machine learning "engine" that we will be using, the "scikit-learn machine learning toolkit," or "scikit-learn toolkit" for short.
  • Finally, we use the code %matplotlib inline to ensure our images display clearly in the Jupyter notebook.

Note that you can also download the Jupyter Notebook for this lesson to follow along.

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