目錄(110章)
倒序
- coverpage
- 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
- Summary
- 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
- Summary
- Chapter 4. Fraud Detection on Spark
- Spark for fraud detection
- Methods for fraud detection
- Feature preparation
- Model estimation
- Model evaluation
- Results explanation
- Deploying fraud detection
- Summary
- Chapter 5. Risk Scoring on Spark
- Spark for risk scoring
- Methods of risk scoring
- Data and feature preparation
- Model estimation
- Model evaluation
- Results explanation
- Deployment
- Summary
- Chapter 6. Churn Prediction on Spark
- Spark for churn prediction
- Methods for churn prediction
- Feature preparation
- Model estimation
- Model evaluation
- Results explanation
- Deployment
- Summary
- Chapter 7. Recommendations on Spark
- Apache Spark for a recommendation engine
- Methods for recommendation
- Data treatment with SPSS
- Model estimation
- Model evaluation
- Recommendation deployment
- Summary
- Chapter 8. Learning Analytics on Spark
- Spark for attrition prediction
- Methods of attrition prediction
- Feature preparation
- Model estimation
- Model evaluation
- Results explanation
- Deployment
- Summary
- Chapter 9. City Analytics on Spark
- Spark for service forecasting
- Data and feature preparation
- Model estimation
- Model evaluation
- Explanations of the results
- Summary
- Chapter 10. Learning Telco Data on Spark
- Spark for using Telco Data
- Methods for learning from Telco Data
- Data and feature development
- Model estimation
- Model evaluation
- Results explanation
- Model deployment
- Summary
- Chapter 11. Modeling Open Data on Spark
- Spark for learning from open data
- Data and feature preparation
- Model estimation
- Results explanation
- Deployment
- Summary
- Index 更新時間：2021-07-16 10:40:12
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