Sign In Start Free Trial
Account

Add to playlist

Create a Playlist

Modal Close icon
You need to login to use this feature.
  • Book Overview & Buying Learning Data Mining with Python
  • Table Of Contents Toc
  • Feedback & Rating feedback
Learning Data Mining with Python

Learning Data Mining with Python

By : Robert Layton
close
close
Learning Data Mining with Python

Learning Data Mining with Python

By: Robert Layton

Overview of this book

This book teaches you to design and develop data mining applications using a variety of datasets, starting with basic classification and affinity analysis. This book covers a large number of libraries available in Python, including the Jupyter Notebook, pandas, scikit-learn, and NLTK. You will gain hands on experience with complex data types including text, images, and graphs. You will also discover object detection using Deep Neural Networks, which is one of the big, difficult areas of machine learning right now. With restructured examples and code samples updated for the latest edition of Python, each chapter of this book introduces you to new algorithms and techniques. By the end of the book, you will have great insights into using Python for data mining and understanding of the algorithms as well as implementations.
Table of Contents (14 chapters)
close
close

Putting it all together

We can now actually run the Naive Bayes classifier using these probabilities. We will do this in a Jupyter Notebook, although this processing itself can be transferred to a mrjob package to be performed at scale.

First, take a look at the models folder that was specified in the last MapReduce job. If the output was more than one file, we can merge the files by just appending them to each other using a command line function from within the models directory:

cat * > model.txt

If you do this, you'll need to update the following code with model.txt as the model filename.

Back to our Notebook, we first import some standard imports we need for our script:

import os 
import re
import numpy as np
from collections import defaultdict
from operator import itemgetter

We again redefine our word search regular expression—if you were doing this in a real application, I recommend centralizing...

Unlock full access

Continue reading for free

A Packt free trial gives you instant online access to our library of over 7000 practical eBooks and videos, constantly updated with the latest in tech

Create a Note

Modal Close icon
You need to login to use this feature.
notes
bookmark search playlist download font-size

Change the font size

margin-width

Change margin width

day-mode

Change background colour

Close icon Search
Country selected

Close icon Your notes and bookmarks

Delete Bookmark

Modal Close icon
Are you sure you want to delete it?
Cancel
Yes, Delete

Delete Note

Modal Close icon
Are you sure you want to delete it?
Cancel
Yes, Delete

Edit Note

Modal Close icon
Write a note (max 255 characters)
Cancel
Update Note

Confirmation

Modal Close icon
claim successful

Buy this book with your credits?

Modal Close icon
Are you sure you want to buy this book with one of your credits?
Close
YES, BUY