更新时间：2021-07-16 13:31:05
封面
版权信息
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Chapter 1. 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
Chapter 2. Classifying with scikit-learn Estimators
scikit-learn estimators
Preprocessing using pipelines
Pipelines
Chapter 3. Predicting Sports Winners with Decision Trees
Loading the dataset
Decision trees
Sports outcome prediction
Random forests
Chapter 4. Recommending Movies Using Affinity Analysis
Affinity analysis
The movie recommendation problem
The Apriori implementation
Extracting association rules
Chapter 5. Extracting Features with Transformers
Feature extraction
Feature selection
Feature creation
Creating your own transformer
Chapter 6. Social Media Insight Using Naive Bayes
Disambiguation
Text transformers
Naive Bayes
Application
Chapter 7. Discovering Accounts to Follow Using Graph Mining
Finding subgraphs
Chapter 8. Beating CAPTCHAs with Neural Networks
Artificial neural networks
Creating the dataset
Training and classifying
Improving accuracy using a dictionary
Chapter 9. Authorship Attribution
Attributing documents to authors
Function words
Support vector machines
Character n-grams
Using the Enron dataset
Chapter 10. Clustering News Articles
Obtaining news articles
Extracting text from arbitrary websites
Grouping news articles
Clustering ensembles
Online learning
Chapter 11. Classifying Objects in Images Using Deep Learning
Object classification
Application scenario and goals
Deep neural networks
GPU optimization
Setting up the environment
Chapter 12. Working with Big Data
Big data
MapReduce
Appendix A. 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
