更新时间：2021-07-16 10:40:12
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Apache Spark Machine Learning Blueprints
Credits
About the Author
About the Reviewer
www.PacktPub.com
eBooks discount offers and more
Preface
What this book covers
What you need for this book
Who this book is for
Conventions
Reader feedback
Customer support
Chapter 1. Spark for Machine Learning
Spark overview and Spark advantages
Spark computing for machine learning
Machine learning algorithms
MLlib
Spark RDD and dataframes
ML workflows and Spark pipelines
ML workflow examples
Spark notebooks
Summary
Chapter 2. Data Preparation for Spark ML
Accessing and loading datasets
Data cleaning
Identity matching
Dataset reorganizing
Dataset joining
Feature extraction
Repeatability and automation
Chapter 3. A Holistic View on Spark
Spark for a holistic view
Methods for a holistic view
Feature preparation
Model estimation
Model evaluation
Results explanation
Deployment
Chapter 4. Fraud Detection on Spark
Spark for fraud detection
Methods for fraud detection
Deploying fraud detection
Chapter 5. Risk Scoring on Spark
Spark for risk scoring
Methods of risk scoring
Data and feature preparation
Chapter 6. Churn Prediction on Spark
Spark for churn prediction
Methods for churn prediction
Chapter 7. Recommendations on Spark
Apache Spark for a recommendation engine
Methods for recommendation
Data treatment with SPSS
Recommendation deployment
Chapter 8. Learning Analytics on Spark
Spark for attrition prediction
Methods of attrition prediction
Chapter 9. City Analytics on Spark
Spark for service forecasting
Explanations of the results
Chapter 10. Learning Telco Data on Spark
Spark for using Telco Data
Methods for learning from Telco Data
Data and feature development
