Neural Networks for Electronics Hobbyists

1. Front Matter

   Pages i-xiv

   PDF

2. Biological Neural Networks

   • Richard McKeon

   Pages 1-17

3. Implementing Neural Networks

   • Richard McKeon

   Pages 19-27

4. Electronic Components

   • Richard McKeon

   Pages 29-54

5. Building the Network

   • Richard McKeon

   Pages 55-73

6. Training with Back Propagation

   • Richard McKeon

   Pages 75-98

7. Training on Other Functions

   • Richard McKeon

   Pages 99-114

8. Where Do We Go from Here?

   • Richard McKeon

   Pages 115-121

9. Back Matter

   Pages 123-139

   PDF

Learn how to implement and build a neural network with this non-technical, project-based book as your guide. As you work through the chapters, you'll build an electronics project, providing a hands-on experience in training a network. 


There are no prerequisites here and you won't see a single line of computer code in this book. Instead, it takes a hardware approach using very simple electronic components. You'll start off with an interesting non-technical introduction to neural networks, and then construct an electronics project. The project isn't complicated, but it illustrates how back propagation can be used to adjust connection strengths or "weights" and train a network. 


By the end of this book, you'll be able to take what you've learned and apply it to your own projects. If you like to tinker around with components and build circuits on a breadboard, Neural Networks for Electronics Hobbyists is the book for you. 


What You'll Learn

• Gain a practical introduction to neural networks
  
• Review techniques for training networks with electrical hardware and supervised learning
  
• Understand how parallel processing differs from standard sequential programming

Who This Book Is For




Anyone interest in neural networks, from electronic hobbyists looking for an interesting project to build, to a layperson with no experience. Programmers familiar with neural networks but have only implemented them using computer code will also benefit from this book.

• Neural Networks
• Artificial Intelligence
• Back propagation
• Machine Learning
• Multi layer
• Feed forward
• Deep learning
• Electronics Projects
• Hidden layer

• Prescott, USA

  Richard McKeon

Richard McKeon has spent the last 40 years designing circuits and building communication networks. Currently living in Prescott, Arizona, Rick spends his time pursuing his passion for writing, playing music, and teaching. Some of his interests also include hiking, treasure hunting, recreational mathematics, photography and experimenting with microcontrollers.

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