更新时间：2021-07-09 20:16:50
封面
版权信息
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
Chapter 3. More AdventureWorks Regression
Introduction to multiple linear regression
Logistic regression
Chapter 4. Traffic Stops – Barking Up the Wrong Tree?
The scientific process
Open data
Hack-4-Good
Chapter 5. Time Out – Obtaining Data
Overview
SQL Server providers
Combining data
Chapter 6. AdventureWorks Redux – k-NN and Naïve Bayes Classifiers
k-Nearest Neighbors (k-NN)
Naïve Bayes
AdventureWorks
Making use of our discoveries
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
Chapter 8. Feature Selection and Optimization
Cleaning data
Selecting data
Overfitting and cross validation
Chapter 9. AdventureWorks Production – Neural Networks
Neural networks
Building the application
Chapter 10. Big Data and IoT
AdventureWorks and the Internet of Bikes
The IoT
Index
