Neural Network Programming with Java

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Neural networks tutorial: Fully Connected 1 [Java]

This makes it a versatile programming language for neural networks. This book gives you a complete walkthrough of the process of developing basic to advanced practical examples based on neural networks with Java.

Neural Network Programming with Java

You will first learn the basics of neural networks and their process of learning. We then focus on what Perceptrons are and their features.


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Next, you will implement self-organizing maps using the concepts you've learned. Furthermore, you will learn about some of the applications that are presented in this book such as weather forecasting, disease diagnosis, customer profiling, and characters recognition OCR. Finally, you will learn methods to optimize and adapt neural networks in real time.

Detalhes do Produto

All the examples generated in the book are provided in the form of illustrative source code, which merges object-oriented programming OOP concepts and neural network features to enhance your learning experience. Vast quantities of data are produced every second. In this context, neural networks become a powerful technique to extract useful knowledge from large amounts of raw, seemingly unrelated data.

One of the most preferred languages for neural network programming is Java as it is easier to write code using it, and most of the most popular neural network packages around already exist for Java.

Neural Network Programming with Java

This makes it a versatile programming language for neural networks. This book gives you a complete walkthrough of the process of developing basic to advanced practical examples based on neural networks with Java.


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  6. You will first learn the basics of neural networks and their process of learning. We then focus on what Perceptrons are and their features. Next, you will implement self-organizing maps using the concepts you've learned.


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    Furthermore, you will learn about some of the applications that are presented in this book such as weather forecasting, disease diagnosis, customer profiling, and characters recognition OCR. Finally, you will learn methods to optimize and adapt neural networks in real time.