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Learning Data Mining with Python

Book Image

Learning Data Mining with Python

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Learning Data Mining with Python
Jul, 2015 | 344 pages
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Table of Contents (20 chapters)
Learning Data Mining with Python
Learning Data Mining with Python
Credits
Credits
About the Author
About the Author
About the Reviewers
About the Reviewers
www.PacktPub.com
www.PacktPub.com
Preface
Preface
Free Chapter
1
Getting Started with Data Mining
Getting Started with Data Mining
Introducing data mining
Using Python and the IPython Notebook
A simple affinity analysis example
A simple classification example
What is classification?
Summary
2
Classifying with scikit-learn Estimators
Classifying with scikit-learn Estimators
scikit-learn estimators
Preprocessing using pipelines
Pipelines
Summary
3
Predicting Sports Winners with Decision Trees
Predicting Sports Winners with Decision Trees
Loading the dataset
Decision trees
Sports outcome prediction
Random forests
Summary
4
Recommending Movies Using Affinity Analysis
Recommending Movies Using Affinity Analysis
Affinity analysis
The movie recommendation problem
The Apriori implementation
Extracting association rules
Summary
5
Extracting Features with Transformers
Extracting Features with Transformers
Feature extraction
Feature selection
Feature creation
Creating your own transformer
Summary
6
Social Media Insight Using Naive Bayes
Social Media Insight Using Naive Bayes
Disambiguation
Text transformers
Naive Bayes
Application
Summary
7
Discovering Accounts to Follow Using Graph Mining
Discovering Accounts to Follow Using Graph Mining
Loading the dataset
Finding subgraphs
Summary
8
Beating CAPTCHAs with Neural Networks
Beating CAPTCHAs with Neural Networks
Artificial neural networks
Creating the dataset
Training and classifying
Improving accuracy using a dictionary
Summary
9
Authorship Attribution
Authorship Attribution
Attributing documents to authors
Function words
Support vector machines
Character n-grams
Using the Enron dataset
Summary
10
Clustering News Articles
Clustering News Articles
Obtaining news articles
Extracting text from arbitrary websites
Grouping news articles
Clustering ensembles
Online learning
Summary
11
Classifying Objects in Images Using Deep Learning
Classifying Objects in Images Using Deep Learning
Object classification
Application scenario and goals
Deep neural networks
GPU optimization
Setting up the environment
Application
Summary
12
Working with Big Data
Working with Big Data
Big data
Application scenario and goals
MapReduce
Application
Summary
Next Steps…
Next Steps…
Chapter 1 – Getting Started with Data Mining
Chapter 2 – Classifying with scikit-learn Estimators
Chapter 3: Predicting Sports Winners with Decision Trees
Chapter 4 – Recommending Movies Using Affinity Analysis
Chapter 5 – Extracting Features with Transformers
Chapter 6 – Social Media Insight Using Naive Bayes
Chapter 7 – Discovering Accounts to Follow Using Graph Mining
Chapter 8 – Beating CAPTCHAs with Neural Networks
Chapter 9 – Authorship Attribution
Chapter 10 – Clustering News Articles
Chapter 11: Classifying Objects in Images Using Deep Learning
Chapter 12 – Working with Big Data
More resources
Index
Index

Credits

Author

Robert Layton

Reviewers

Asad Ahamad

P Ashwin

Christophe Van Gysel

Edward C. Delaporte V

Commissioning Editor

Taron Pereira

Acquisition Editor

James Jones

Content Development Editor

Siddhesh Salvi

Technical Editor

Naveenkumar Jain

Copy Editors

Roshni Banerjee

Trishya Hajare

Project Coordinator

Nidhi Joshi

Proofreader

Safis Editing

Indexer

Priya Sane

Graphics

Sheetal Aute

Production Coordinator

Nitesh Thakur

Cover Work

Nitesh Thakur

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