what activation function

ObjectiveFor deep learning, novice I recommend to see UFLDL first, do not do assignment words, one or two nights can be read. After all, convolution, pooling what is not a particularly mysterious thing. The course is concise, sharply, and points out

bp neural network in BP for back propagation shorthand, the earliest it was by Rumelhart, McCelland and other scientists in 1986, Rumelhart and in nature published a very famous article "Learning R Epresentations by back-propagating errors ". With

In front of us, we talked about the DNN, and the special case of DNN. CNN's model and forward backward propagation algorithms are forward feedback, and the output of the model has no correlation with the model itself. Today we discuss another type

"Convolutional neural Networks-evolutionary history" from Lenet to Alexnet This blog is "convolutional neural network-evolutionary history" of the first part of "from Lenet to Alexnet" If you want to reprint, please attach this article

The basic knowledge of neural network can refer to the basic knowledge of neural network, the basic thing is very good, and then the solution of the parameters in the neural network is explained. Some variables are explained: The circle labeled ""

The basic structure of alexnetAlexnet is composed of 5 convolutional layers and three fully connected layers, a total of 8 weight layers (the pooling layer is not a weight layer because it has no parameters), wherein the RELU activation function on

first, the origin of the reverse transmissionBefore we start the DL study, we need to make a simple explanation of the ann-artificial neural network and BP algorithm.On the structure of Ann, I no longer say that there is a large number of online

Artificial neural Network (Artificial Neural Network, Ann) is a hotspot in the field of artificial intelligence since the 1980s. It is also the basis of various neural network models at present. This paper mainly studies the BPNN model. What is a

0. Statement It was a failed job, and I underestimated the role of scale/shift in batch normalization. Details in the fourth quarter, please take a warning. First, the preface There is an explanation for the function of the neural network: It is a

1. Preface In the process of learning deep learning, the main reference is four documents: the University of Taiwan's machine learning skills open course; Andrew ng's deep learning tutorial; Li Feifei's CNN tutorial; Caffe's official website

"Matlab Neural network Programming" Chemical Industry Press book notesThe fourth Chapter 4.3 BP propagation Network of forward type neural network This article is "MATLAB Neural network Programming" book reading notes, which involves the source code,

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

Keras is a python library for deep learning that contains efficient numerical libraries Theano and TensorFlow. The purpose of this article is to learn how to load data from CSV and make it available for keras use, how to model the data of

Neural Network Neurons The basic structure of neurons is as follows: Input: The input of the neuron is a vector x=[x0,x1,x2,x3,..., xn] x=[x_0,x_1,x_2,x_3,..., x_n], where x1,x2,x3,..., xn x_1,x_2,x_3,..., x_n represents the n characteristics

cs231n-assignment 1-q4-two-layer Neural Network Written: Guo Chengkun concept of Fanli slyned proofreading: Maoli He hui to and audit: cold Small Yang 1 Quests In this exercise, we will implement a fully connected neural network classifier and

This brief introduction to the MSRA initialization method is also derived from He Keming paper delving deep into rectifiers:surpassing human-level performance on ImageNet Classification ". Motivation MSRA initialization

Before I have been using Theano, the previous five deeplearning related articles are also learning Theano some notes, at that time already feel Theano use up a little trouble, sometimes want to achieve a new structure, it will take a lot of time to

Welcome reprint, Reprint Please specify: This article from Bin column Blog.csdn.net/xbinworld.Technical Exchange QQ Group: 433250724, Welcome to the algorithm, technology interested students to join.Recently, the next few posts will go back to the

Reference. Krizhevsky A, Sutskever I, Hinton G E. ImageNet classification with deep convolutional neural Networks [J]. Advances in neural information processing Systems, 2012, 25 (2): 2012.https://code.google.com/p/cuda-convnet/ Say

The introduction of convolution neural network Original address : http://blog.csdn.net/hjimce/article/details/47323463 Author : HJIMCE Convolution neural network algorithm is the algorithm of n years ago, in recent years, because the depth learning