BP (Back Propagation)The network was proposed by a team of scientists headed by Rumelhart and mccelland in 1986. It is a multi-layer feed-forward Network trained by the error inverse propagation algorithm and is one of the most widely used neural network models. The BP network
Author: one person 1. Deep neural networks are suitable for any field
Depth neural network (deep neural Networks,DNN has made breakthrough advances in image classification, speech recognition, and natural language processing over the past few years. The application in practice has proved that it can be used as a very e
Reprint: http://www.cnblogs.com/zhijianliutang/p/4067795.htmlObjectiveFor some time without our Microsoft Data Mining algorithm series, recently a little busy, in view of the last article of the Neural Network analysis algorithm theory, this article will be a real, of course, before we summed up the other Microsoft a series of algorithms, in order to facilitate everyone to read, I have specially compiled a
The previous section in"machine learning from logistic to neural network algorithm", we have introduced the origin and construction of neural network algorithm from the principle, and programmed the simple neural network to classi
Neural network and deep learning the book has been read several times, but each time there will be a different harvest. DL field of paper, every day there will be a lot of new idea out, I think, in-depth reading classic books and paper, must be able to find Remian open problems, so there is a different perspective.Ps:blog is a summary of important contents in the main extract book.Summary section
Weight vector W, training sample X1. Initialize the weight vector to 0, or initialize each component to any decimal between [0,1]2. Input the training sample into the Perceptron to get the classification result (-1 or 1)3. Update weight vectors based on classification resultsPerceptron algorithm for Tuyi data samples that are linearly delimitedMachine learning--perceptron data classification algorithm step (MU-class network-to achieve a simple
Pybrain is a well-known Python neural network library, today I used it to do an experiment, referring to this blog, thanks to the original author, gave a specific implementation, the code can be directly copied to run.Our main problems are as follows:First we give a function to construct the dataset that is required to generate this problem .
Def generate_data (): "" "
generate original data of U and Y
Abstract: With the development of computational intelligence, artificial neural network has been developed. The industry now considers that it may not be appropriate to classify neural networks (NN) in artificial intelligence (AI), and that the classification of computational Intelligence (CI) can explain the nature of the problem. Some topics in evolutionary com
Reprint: http://www.cnblogs.com/jzhlin/archive/2012/07/30/bp_c.html
In the last article, we introduce the basic model of BP neural network, some terms in the model and the mathematical analysis of the model, and have a preliminary understanding of its principle. Then how to use the program language to specifically implement it, will be the next issue we need to discuss. This paper chooses the C language to
Artificial neural network is a simulation of the biological nervous system. Its information processing function is determined by the input and output characteristics (activation characteristics) of the network Unit (neuron), the topology of the network (the connection mode of the neuron), the connection weight (synapti
Civilization number" and the Central State organ "youth civilization" title.Smart Apps
Intelligent processing is the core problem
20w Human brain Power consumption
Multilayer large-scale neural network ≈ convolutional Neural Network + LRM (different feature map extracts different features to complete
Neural network and deep learning the book has been read several times, but each time there will be a different harvest.The paper of DL field is changing rapidly. There's a lot of new idea coming out every day, I think. In-depth reading of classic books and paper, you will be able to find Remian open problems. So there's a different perspective.Ps:blog is a summary of important contents in the main extract b
realization of Image search algorithm based on convolutional neural network If you use this name to search for papers, there must be a lot. Why, because from a theoretical point of view, convolutional neural networks are ideal for finding similar places in images. Think about it, a lot of Daniel, calf, and micro-ox articles are about how to find similar images fr
Introduction to convolutional Neural Networks
Convolutional neural network is a multi-layer neural network that specializes in processing machine learning problems related to images, especially big images.
The most typical convolutional
convolutional Neural Network Primer (1)
Original address : http://blog.csdn.net/hjimce/article/details/47323463
Author : HJIMCE
convolutional Neural Network algorithm is an n-year-old algorithm, only in recent years because of deep learning related algorithms for the training of multi-layered networks to provide a new
The article was transferred from the deep learning public numberDeep learning is a new field in machine learning that is motivated by the establishment and simulation of a neural network for analytical learning of the human brain, which mimics the mechanisms of the human brain to interpret data, examples, sounds and texts. Deep learning is a kind of unsupervised learning.The concept of deep learning derives
Neural networks have been very hot, there has been a period of depression, now because of deep learning reasons to continue to fire up. There are many kinds of neural networks: forward transmission network, reverse transmission network, recurrent neural
Open source Artificial Neural Network Computing Library FANN Learning Note 1These days machine learning is very fire, neural network is the machine learning algorithm is a more important one. This time I also took some effort, learned a little fur, by the way to do some study notes.There are many textbooks about the ba
NIPS 2016 article: Intel China Research Institute on Neural Network compression algorithm of the latest achievementsHttp://www.leiphone.com/news/201609/OzDFhW8CX4YWt369.htmlIntel China Research Institute's latest achievement in the field of deep learning--"dynamic surgery" algorithm 2016-09-05 11:33 reproduced pink Bear 0 reviewsLei Feng Net press: This article is the latest research results of Intel China
Wunda Depth Learning lesson five programming question one
Import Module
Import NumPy as NP from
rnn_utils Import *
Circular Neural Network small unit forward propagation
# graded Function:rnn_cell_forward def rnn_cell_forward (XT, A_prev, parameters): "" "Implements a single forward Step of the Rnn-cell as described into Figure (2) arguments:xt--Your input dat
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