更新时间：2021-07-23 16:41:20
封面
Title Page
Copyright and Credits
Hands-On Neural Network Programming with C#
Dedication
Packt Upsell
Why subscribe?
Packt.com
Contributors
About the author
About the reviewers
Packt is searching for authors like you
Preface
Who this book is for
What this book covers
To get the most out of this book
Download the example code files
Download the color images
Code in Action
Conventions used
Get in touch
Reviews
A Quick Refresher
Technical requirements
Neural network overview
Neural network training
A visual guide to neural networks
The role of neural networks in today's enterprises
Types of learning
Supervised learning
Unsupervised learning
Reinforcement learning
Understanding perceptrons
Is this useful?
Understanding activation functions
Visual activation function plotting
Function plotting
Understanding back propagation
Forward and back propagation differences
Summary
References
Building Our First Neural Network Together
Our neural network
Synapses
Neurons
Forward propagation
Sigmoid function
Backward propagation
Calculating errors
Calculating a gradient
Updating weights
Calculating values
Neural network functions
Creating a new network
Importing an existing network
Importing datasets
Testing the network
Exporting the network
Training the network
Computing forward propagation
Exporting a dataset
The neural network
Neuron connection
Examples
Training to a minimum
Training to a maximum
Decision Trees and Random Forests
Decision trees
Decision tree advantages
Decision tree disadvantages
When should we use a decision tree?
Random forests
Random forest advantages
Random forest disadvantages
When should we use a random forest?
SharpLearning
Terminology
Loading and saving models
Example code and applications
Saving a model
Mean squared error regression metric
F1 score
Optimizations
Sample application 1
The code
Sample application 2 – wine quality
Face and Motion Detection
Facial detection
Motion detection
Code
