MATLAB神经网络入门:实战设计与应用

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《使用MATLAB构建神经网络:Marvin L.的全面指南》是一本专为熟悉MATLAB编程的初学者准备的神经网络入门教材。该书循序渐进地讲解了神经网络的基础概念,特别强调了如何利用MATLAB这一强大的工具进行实际操作。作者Marvin L.引导读者从机器学习基础知识入手,逐步过渡到神经网络设计、配置、权重和偏置初始化、训练以及网络的应用。 书中核心内容包括神经网络设计过程中的四个关键步骤:数据收集、创建网络、配置网络和使用网络。作者特别关注了第2步(创建网络)、第3步(配置网络)、第5步(训练网络)和第7步(使用网络),因为这些步骤涉及到了神经网络的基本原理。第1步(数据收集)虽然重要,但通常在神经网络工具箱软件框架之外讨论,会在后续章节“多层网络和反向传播训练”中展开。 神经网络设计过程中,MATLAB的神经网络工具箱通过网络对象来存储网络的所有定义信息。本书详细介绍了神经网络的基本组成部分,如输入层、隐藏层和输出层,以及它们如何在网络对象中被创建和组织。此外,还包括了如何根据问题类型调整网络结构,即配置网络,使之适应所面临的实际问题。 在创建好网络后,下一步是对其进行配置,这涉及到调整网络参数以适应训练数据,如设定学习率、激活函数等。接着,第5步训练网络则涉及使用反向传播算法来优化权重和偏置,以减小预测误差。最后,完成训练的网络可以用于处理新数据,这就是第7步网络的使用。 通过阅读本书,读者不仅能掌握神经网络的基础知识,还能了解如何在MATLAB环境中高效地实现和应用这些技术,解决实际中的大数据分析、智能机器人和其他复杂问题。书中对机器学习的深入探讨和智能数据分析方面的实践,有助于读者理解这个领域更为复杂的方面,并在实际项目中展现出更高的智能水平。《使用MATLAB构建神经网络》是一本实用且深入的教程,对于希望在这个领域进一步发展的学习者来说,是一份不可或缺的参考资料。
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Uncover the power of artificial neural networks by implementing them through R code. About This Book Develop a strong background in neural networks with R, to implement them in your applications Build smart systems using the power of deep learning Real-world case studies to illustrate the power of neural network models Who This Book Is For This book is intended for anyone who has a statistical background with knowledge in R and wants to work with neural networks to get better results from complex data. If you are interested in artificial intelligence and deep learning and you want to level up, then this book is what you need! What You Will Learn Set up R packages for neural networks and deep learning Understand the core concepts of artificial neural networks Understand neurons, perceptrons, bias, weights, and activation functions Implement supervised and unsupervised machine learning in R for neural networks Predict and classify data automatically using neural networks Evaluate and fine-tune the models you build. In Detail Neural networks are one of the most fascinating machine learning models for solving complex computational problems efficiently. Neural networks are used to solve wide range of problems in different areas of AI and machine learning. This book explains the niche aspects of neural networking and provides you with foundation to get started with advanced topics. The book begins with neural network design using the neural net package, then you'll build a solid foundation knowledge of how a neural network learns from data, Table of Contents Chapter 1. Neural Network and Artificial Intelligence Concepts Chapter 2. Learning Process in Neural Networks Chapter 3. Deep Learning Using Multilayer Neural Networks Chapter 4. Perceptron Neural Network Modeling – Basic Models Chapter 5. Training and Visualizing a Neural Network in R Chapter 6. Recurrent and Convolutional Neural Networks Chapter 7. Use Cases of Neural Networks – Advanced Topics