搜索资源列表
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
libORF-master
- 针对各种机器学习，深度学习领域的一个matlab工具包-A machine learning library focused on deep learning.Following algorithms and models are provided along with some static utility classes: - Naive Bayes, Linear Regression, Logistic Regression, Softmax Regression, Linear S
DeepLearning-master
- 机器学习领域中的深度学习资料，其中包括了各种语言的版本，有matlab，C语言，c++等。代码中包括了深度学习的一些模型，如栈式自动编码机，深度信念网-It s about deep learning in machine learning, including some model with different programming language. The models are stacked auto encoders, deep belief nets and so on
DeepLearning-master
- 深度学习的概念源于人工神经网络的研究。含多隐层的多层感知器就是一种深度学习结构。深度学习通过组合低层特征形成更加抽象的高层表示属性类别或特征，以发现数据的分布式特征表示。[1] 深度学习的概念由Hinton等人于2006年提出。基于深信度网(DBN)提出非监督贪心逐层训练算法，为解决深层结构相关的优化难题带来希望，随后提出多层自动编码器深层结构。此外Lecun等人提出的卷积神经网络是第一个真正多层结构学习算法，它利用空间相对关系减少参数数目以提高训练性能。[1] 深度学习是机器
paper1
- A Comparative Evaluation of Deep Belief Nets in Semi-supervised Learning
paper2
- A fast learning algorithm for deep belief nets
deepnet-master
- Nitish Srivastava University of Toronto.利用GPU训练深度学习算法-Implementation of some deep learning algorithms. Nitish Srivastava University of Toronto. GPU-based python implementation of 1. Feed-forward Neural Nets 2. Restricted Boltzmann Machines
PG_DEEP-master
- A fast learning algorithm for deep belief nets 文章代码-2006 A fast learning algorithm for deep belief nets
Sparse-Autoencoder
- 稀疏编码算法是一种无监督学习方法，它用来寻找一组“超完备”基向量来更高效地表示样本数据-2006 A fast learning algorithm for deep belief nets
dbn
- 深度置信网，经过调试，运行没有问题。运行时有点占内存，速度稍慢。-Deep Belief Nets, Restricted Boltzmann Maching
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
RBM-DBN
- 有限玻尔兹曼机、深度置信网的Matlab实现，用mnist数据进行验证，对理解深度学习原理有帮助。(A Finite Boltzmann machine and deep belief network are implemented in MATLAB and verified with MNIST data. It is helpful to understand the principle of deep learning.)