搜索资源列表
Deep-Learning
- 实现常见的深度神经网络的学习过程，适合初学者学习使用，也可以进一步开发使用，具有较高的学习价值和学术价值。-The depth to achieve common neural network learning process, suitable for beginners to learn to use, can be further developed to use, with high learning and academic values.
Deep-Learning-Note
- 对学习深度神经网络很有用的资料，深入浅出地对相关的知识点进行了解析，值得一阅-Very useful for learning neural network, explain profound theories in simple language to analyze the related knowledge points, worth reading
Deep-Learning-Toolbox
- 深度学习matlab工具箱,包括深度deep belief nets,stacked autoencoder,convolutional neural nets等网络。-Matlab/Octave toolbox for deep learning. Includes Deep Belief Nets, Stacked Autoencoders, Convolutional Neural Nets, Convolutional Autoencoders and vanilla Neural Ne
deep-neural-network
- 由微软提供的深度学习资料，包括了各种深度学习算法和开源工具包的使用。-deep learning toolkit
Deep-neural-network
- Deep neural network Deep neural network-Deep neural networkDeep neural network
DeepNeuralNetwork20150129
- deep neural learning
neural-networks-and-deep-learning-master
- 用不同的方法实现了神经网络（没有用第三方库，就是用numpy等实现的，对于初学者来说是不错的深入了解神经网络的素材）(Using different methods to achieve the neural network (not using third square libraries, that is, using numpy and so on, for beginners is a good understanding of the neural network material))
deep-go_20170125
- web端直接打开对战，主要是人机对战，机器人拥有9级棋力(Play Go Against a Deep Neural Network)
DeepNeuralNetwork20160805
- this files contain the matlab code for deep neural netwoek
neural-networks-and-deep-learning-master
- neural-networks-and-deep-learning-master
neural face recognition
- This pdf introduces a method of face recognition untitled Face Recognition with Very Deep Neural Networks
Learning Deep Architectures for AI
- 一本关于深度架构学习算法，尤其是用来构造更深层模型的非监督学习的单层模型。(Theoretical results suggest that in order to learn the kind of com- plicated functions that can represent high-level abstractions (e.g., in vision, language, and other AI-level tasks), one may need deep archite
AI Bible(Deep Learning)
- 随后该书分为三部分，第一部分是应用数学和机器学习基础，当初步具有上述理论基础后，才算叩开深度学习的大门。第二部分是深层网络的现代实践。第三部分是深度学习的理论研究，适用于想要执果索因、深入学习神经网络内在原理的研究人员学习。(The book is divided into three parts, the first part is the application of mathematical and machine learning based. When initially with t
Dynamic_Deep_Neural_Networks
- We introduce Dynamic Deep Neural Networks (D2NN), a new type of feed-forward deep neural network that allows selective execution. Given an input, only a subset of D2NN neurons are executed, and the particular subset is determined by the D2NN itse
Deep Learning Based Communication Over the Air
- 通信系统的端到端学习是a 引人入胜的新颖概念迄今为止仅被验证 模拟基于块的传输。它允许学习 发射机和接收机实现为深度神经网络 （NN），它们针对任意可区分的端到端进行了优化 performancemetric，例如块错误率（BLER）。在本文中，我们 证明无线传输是可能的：我们建造， 训练，并运行完整的通讯系统 的神经网络使用非同步的现成软件定义无线电 和开源深度学习软件库。(End-to-end learning of communications systems is a
py3-neural-network-master
- Python3.6实现神经网络算法，经过mnist数据集测试后表现良好，准确率约为95%-96%。 /src 为源代码 /data为mnist算集(This is a code samples for "Neural Networks and Deep Learning" using python3.)
cifar10_tutorial
- 非常适合入门的一个深度学习图片分类例程！(Very suitable for beginners to learn a deep picture classification routines!)
Neural-Networks-and-Deep-Learning-A-Textbook
- Charu C. Aggarwal Neural Networks and Deep Learning
Deep Neural Network
- 深度神经网络训练过程中：首先是进行初始化，根据需求设置神经网络的基本结构；然后进行前向传递（feedforward），层与层之间进行传递，求得误差；然后进行反向传播（back propogation），根据误差最小化原则，使用随机梯度下降法，对各个参数进行求导，确定下降方向，对各个参数进行更新(In the training process of deep neural network, firstly, initialization is carried out, and the basic
deep-learning
- Dynamic resource allocation dqn