a tuple (ipaddr,port)Sk.fileno ()file descriptor for socketsSecond, get some address and host nameThe socket module provides several functions for working with host names and addresses.Socket.gethostname ()GetHostName () returns the host name of the computer on which the program is runningSocket.gethostbyname (' www.jb51.net ')gethostbyname (name) attempts to interpret the given host name as an IP address.GETHOSTBYNAME_EX (name)It returns a tuple of three elements, namely a list of the primary
at the same time. We pass in a matrix (instead of a vector) at the input, and the columns of this matrix represent the vectors in this batch. In forward propagation, each node multiplies the input by multiplying the weight matrix, adding a bias matrix, and applying sigmoid functions to get the output, which is also calculated in a similar way when it is transmitted in reverse. Explicitly write this method of reverse propagation and modify network.py it so that it is calculated using this comple
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
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
0-Background
This paper introduces the deep convolution neural network based on residual network, residual Networks (resnets).Theoretically, the more neural network layers, the more complex model functions can be represented. CNN can extract the features of low/mid/high-lev
Constructing neural network with Keras
Keras is one of the most popular depth learning libraries, making great contributions to the commercialization of artificial intelligence. It's very simple to use, allowing you to build a powerful neural network with a few lines of code. In this article, you will learn how to bui
In this paper, a simple handwriting recognition system is realized by BP neural network.First, the basic knowledge1 environmentpython2.7Need to numpy and other librariesCan be installed with sudo apt-get install python-2 Neural Network principleHttp://www.hankcs.com/ml/back-propagation-
A course of recurrent neural Network (1)-RNN Introduction
source:http://www.wildml.com/2015/09/recurrent-neural-networks-tutorial-part-1-introduction-to-rnns/
As a popular model, recurrent neural Network (Rnns) has shown great application prospect in NLP. Despite the recent
communication more simply and intuitively.Reminder: If your network speed is slow, loading GIF animation may be slow. Please wait.2. About the authorQian wenpin (old money): Graduated from Huazhong University of Science and Technology in computer science and technology, and has been a veteran of Internet distributed high Concurrency Technology for ten years. Currently, he is a senior backend engineer of shouxi technology. Proficient in Java,
Sample program Download: Http://files.cnblogs.com/gpcuster/ANN3.rarIf you have questions, please refer to the FAQIf you do not find a satisfactory answer, you can leave a message below:)0 CatalogueIntroduction to Artificial neural network (1)--application of single-layer artificial neural networkIntroduction to Artificial neu
network);5. Rnns is implemented based on Python and Theano, including some common Rnns models.
Unlike traditional Fnns (Feed-forward neural Networks, forward feedback neural networks), Rnns introduces a directional loop that can handle the problems associated with those inputs. The directional loop structure is shown
Deep learning "engine" contention: GPU acceleration or a proprietary neural network chip?Deep Learning (Deepin learning) has swept the world in the past two years, the driving role of big data and high-performance computing platform is very important, can be described as deep learning "fuel" and "engine", GPU is engine engine, basic all deep learning computing platform with GPU acceleration. At the same tim
example:This by-phase multiplication is sometimes called the Hadamard product. A good matrix library usually provides a fast implementation of the Hadamard product, which is handy for implementing reverse propagation.Four equations behind the reverse propagationReverse propagation is about understanding how weights and biases change when a network changes the loss function. Ultimately, this means calculati
This paper aims at constructing probabilistic language model of Chinese based on Fudan Chinese corpus and neural network model.A goal of the statistical language model is to find the joint distribution of different words in the sentence, that is to find the probability of the occurrence of a word sequence, a well-trained statistical language model can be used in speech recognition, Chinese input method, mac
convolutional Neural Network (convolutional neural network,cnn), weighted sharing (weight sharing) network structure reduces the complexity of the model and reduces the number of weights, which is the hotspot of speech analysis and image recognition. No artificial feature ex
}) //先训练D z= np.random.random(M) sess.run(opt_g, {z_node: z}) //在训练GThe above code is an example of the tensorflow implementation of generating Gaussian distributions against NN.The installation and operation of fellow thesis code of Daniel GoodGoodfellow, the author of the Anti-network, also open up his own code.(1) Project linkAdversarial links(2) Download and dependent library
Keras Introduction?? Keras is an open-source, high-level neural network API written by pure Python that can be based on TensorFlow, Theano, Mxnet, and CNTK. Keras is born to support rapid experimentation and can quickly turn your idea into a result. The Python version for Keras is:
Series PrefaceReference documents:
Rnnlm-recurrent Neural Network Language Modeling Toolkit (click here to read)
Recurrent neural network based language model (click here to read)
EXTENSIONS of recurrent neural NETWORK LAN
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