LAMSTAR-1 and LAMSTAR-2 Neural Networks Other Neural Networks for Deep Learning Case Studies Concluding Comments Problems Appendices to Case Studies of Chapter 8 Author Index Subject Index Readership: We recommend Related Books Graph-Theoretic Techniques for Web Content Mining ...
【4.1.4】深层神经网络(Deep Neural Networks) 一、 深层神经网络(Deep L-layer neural network) 目前为止我们学习了只有一个单独隐藏层的神经网络的正向传播和反向传播,还有逻辑回归,并且你还学到了向量化,这在随机初始化权重时是很重要。 本周所要做的是把这些理念集合起来,就可以执行你自己的深度神经网络。 复...
深度神经网络(deep neural network)是机器学习模型的一种,而用模型拟合数据的过程被称为深度学习(deep learning)。在撰写此文章时,深度神经网络是最强大、最实用的机器学习模型,并且在日常生活中经常遇到。使用自然语言处理算法(Natural Language Processing,NLP)将一种语言翻译到另一种语言、使用计算机视觉系统(Computer...
Understand how deep networks evolved from neural network fundamentals Explore the major deep network architectures, including Convolutional and Recurrent Learn how to map specific deep networks to the right problem Walk through the fundamentals of tuning general neural networks and specific deep network arc...
Learn Deep Learning in 2023 with best Deep Learning courses, best Deep Learning tutorials & best Deep Learning books in 2023
Deep learning, a powerful set of techniques for learning in neural networks Neural networks and deep learning currently provide the best solutions to many problems in image recognition, speech recognition, and natural language processing. This book will teach you many of the core concepts behind neur...
Deep neural network acoustic models produce substantial gains in large vocabulary continuous speech recognition systems. Emerging work with rectified linea... Maas,Hannun 被引量: 1270发表: 0年 Sequence to Sequence Learning with Neural Networks Deep Neural Networks (DNNs) are powerful models that have...
Aspiringdatascientistsandmachinelearningexpertswhohavelimitedornoexposuretodeeplearningwillfindthisbooktobeveryuseful.Ifyouarelookingforaresourcethatgetsyouupandrunningwiththefundamentalsofdeeplearningandneuralnetworks,thisbookisforyou.AsthemodelsinthebookaretrainedusingthepopularPython-basedlibrariessuchasTensorflowand...
generally not broadly understood, and which now acts as a sign of how far the expectations and general understanding of neural networks has come in a short time, Deep Learning sets out early on to dispel the "neural network as a biological brain" fallacy immediately in the books' introduction...
teachingyouhowtoleverageTensorFlow’scapabilitiestoperformefficientimageprocessingusingthepowerofdeeplearning.Withthehelpofthisbook,youwillgettogripswiththedifferentparadigmsofperformingdeeplearningsuchasdeepneuralnetsandconvolutionalneuralnetworks,followedbyunderstandinghowtheycanbeimplementedusingTensorFlow.Bytheendofthisbook...