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Hands-On Neural Network Programming with C#

You're reading from   Hands-On Neural Network Programming with C# Add powerful neural network capabilities to your C# enterprise applications

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Product type Paperback
Published in Sep 2018
Publisher Packt
ISBN-13 9781789612011
Length 328 pages
Edition 1st Edition
Languages
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Author (1):
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Matt Cole Matt Cole
Author Profile Icon Matt Cole
Matt Cole
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Table of Contents (16) Chapters Close

Preface 1. A Quick Refresher 2. Building Our First Neural Network Together FREE CHAPTER 3. Decision Trees and Random Forests 4. Face and Motion Detection 5. Training CNNs Using ConvNetSharp 6. Training Autoencoders Using RNNSharp 7. Replacing Back Propagation with PSO 8. Function Optimizations: How and Why 9. Finding Optimal Parameters 10. Object Detection with TensorFlowSharp 11. Time Series Prediction and LSTM Using CNTK 12. GRUs Compared to LSTMs, RNNs, and Feedforward networks 13. Activation Function Timings
14. Function Optimization Reference 15. Other Books You May Enjoy

Function minimization and maximization

Function minimization and maximization are the process of finding the smallest and largest value of a given function. Let's talk briefly about that value.

If the value is within a given range, then it is called the local extrema; if it is within the entire domain of a function then it is called the global extrema. Let's say we have a function f, and it's defined against a domain X. The maximum, or global, point at x* is f(x*) is greater than or equal to f(x) for all x in the domain X. Conversely, the function's global minimum point at x* is f(x*) is less than or equal to f(x) for all x in the domain X.

In a simpler fashion, the maximum point is also called the maximum value, and the minimum point is called the minimum value, of the function. The global maximum or minimum is either the highest or lowest function value in...

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