Название: Neural Networks: Introduction to Artificial Neurons, Backpropagation and Multilayer Feedforward Neural Networks with Real-World Applications (Advanced Data Analytics Book 2) Автор: Morgan Maynard Издательство: Independently published Год: 2017 Дата выхода на Amazon: May 18, 2020 Язык: английский Формат: pdf, azw3 Размер: 10.1 MB
Do You Know Why Software Engineers Study the Human Brain?
Software Engineers recognize that computers can process and store much more data than humans, yet even supercomputers can’t carry out tasks that come easily to the human brain, such as facial recognition or natural language processing. MIT’s state-of-the-art research facility, named “Centre for Brains, Minds and Machines”, is a perfect testimonial to this fundamental interaction between the human brain and computers in today’s world.
Hence engineers began studying the processes and structures of our human brains, hoping to build a computer model of its functions – Neural Networks were born. These models are very simplistic, but fundamentally replicate the inner structures of our own brains downright to the functions of an individual neuron.
In this book I show you exactly how engineres model the inner functions and structure of the human brains, covering the fundamental mathematical equations and underlying concepts. In particular, you will learn about:
How to Build a Computer model of a Brain Cell (or Neuron) The Fundamental properties of a Neural Network Multilayer Forward Networks Using the Backpropagation algorithm to learn and adapt Counter Propagation Networks How to train a Neural network (validation and testing techniques to avoid overfitting)
Contents: Chapter 1 – Introduction Chapter 2 – About the Series Chapter 3 – A Brief Overview Chapter 4 – From Deep Blue to AlphaGo Chapter 5 – The process of Learning Chapter 6 – Biological inspiration Chapter 7 – The Neuron Chapter 8 – Perceptron Chapter 9 – Multilayer Feedforward Networks Chapter 10 – Backpropagation Chapter 11 – Alternative Architectures Chapter 12 – Deeper Look at Training Bonus Chapter – Foundations of Markov Models (Extract from Book 3 of the Series) Conclusion
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