目錄(63章)
倒序
- 封面
- 版權信息
- Credits
- About the Author
- Acknowledgments
- About the Reviewers
- www.PacktPub.com
- Preface
- Chapter 1. Welcome to Machine Learning Using the .NET Framework
- What is machine learning?
- Why .NET?
- What version of the .NET Framework are we using?
- Why write your own?
- Why open data?
- Why F#?
- Getting ready for machine learning
- Third-party libraries
- Summary
- Chapter 2. AdventureWorks Regression
- Simple linear regression
- Math.NET
- Accord.NET
- AdventureWorks app
- Summary
- Chapter 3. More AdventureWorks Regression
- Introduction to multiple linear regression
- Logistic regression
- Summary
- Chapter 4. Traffic Stops – Barking Up the Wrong Tree?
- The scientific process
- Open data
- Hack-4-Good
- Summary
- Chapter 5. Time Out – Obtaining Data
- Overview
- SQL Server providers
- Combining data
- Summary
- Chapter 6. AdventureWorks Redux – k-NN and Na?ve Bayes Classifiers
- k-Nearest Neighbors (k-NN)
- Na?ve Bayes
- AdventureWorks
- Making use of our discoveries
- Summary
- Chapter 7. Traffic Stops and Crash Locations – When Two Datasets Are Better Than One
- Unsupervised learning
- Traffic stop and crash exploration
- The Code-4-Good application
- Summary
- Chapter 8. Feature Selection and Optimization
- Cleaning data
- Selecting data
- Overfitting and cross validation
- Summary
- Chapter 9. AdventureWorks Production – Neural Networks
- Neural networks
- Building the application
- Summary
- Chapter 10. Big Data and IoT
- AdventureWorks and the Internet of Bikes
- The IoT
- Summary
- Index 更新時間：2021-07-09 20:16:50
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