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Hands-On Neural Networks

Hands-On Neural Networks

By : Leonardo De Marchi, Laura Mitchell
3.5 (2)
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Hands-On Neural Networks

Hands-On Neural Networks

3.5 (2)
By: Leonardo De Marchi, Laura Mitchell

Overview of this book

Neural networks play a very important role in deep learning and artificial intelligence (AI), with applications in a wide variety of domains, right from medical diagnosis, to financial forecasting, and even machine diagnostics. Hands-On Neural Networks is designed to guide you through learning about neural networks in a practical way. The book will get you started by giving you a brief introduction to perceptron networks. You will then gain insights into machine learning and also understand what the future of AI could look like. Next, you will study how embeddings can be used to process textual data and the role of long short-term memory networks (LSTMs) in helping you solve common natural language processing (NLP) problems. The later chapters will demonstrate how you can implement advanced concepts including transfer learning, generative adversarial networks (GANs), autoencoders, and reinforcement learning. Finally, you can look forward to further content on the latest advancements in the field of neural networks. By the end of this book, you will have the skills you need to build, train, and optimize your own neural network model that can be used to provide predictable solutions.
Table of Contents (16 chapters)
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1
Section 1: Getting Started
4
Section 2: Deep Learning Applications
9
Section 3: Advanced Applications

History of AI

The idea of AI, entailing machine that can think without human help, is surprisingly old. It can be dated back to the Indian philosophies of Charvaka, from around 1,500 BC.

The basis of AI is the philosophical concept that human reasoning can be mapped into a mechanical process. We can find this process in many civilizations in the first millennium BC, in particular in Greek philosophers such as Aristotle and Euclid.

Philosophers and mathematicians, such as Leibniz and Hobbes, in the 17th century explored the possibility that all of a human being's rational thoughts could be mapped into an algebraic or geometric system.

Only at the beginning of the 20th century was the limits defined of what mathematics and logic can accomplish and how far mathematical reasoning can be abstracted. It was at that time that the mathematician Alan Turing defined the Turing machine...

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