what activation function

I. Why sequence models? (1) sequence models are widely used in speech recognition, music generation, sentiment analysis, DNA sequence analysis, machine translation, video behavior recognition, Named Entity recognition, and many other fields.(2) The

Deep Learning Neural Network pure C language basic edition, deep Neural Network C Language Today, Deep Learning has become a field of fire, and the performance of Deep Learning Neural Networks (DNN) in the field of computer vision is remarkable. Of

Deep Learning (depth learning) Learning notes finishing Series[Email protected]Http://blog.csdn.net/zouxy09ZouxyVersion 1.0 2013-04-08Statement:1) The Deep Learning Learning Series is a collection of information from the online very big Daniel and

I. CNN's biological principles, applications and advantagesCNN based on the local characteristics of the human eye Vision nerve design, widely used in image image, pattern recognition, machine vision and speech recognition, it on the image

This paper is based on the first two, multilayer perceptron and its BP algorithm (multi-layer Perceptron) and recurrent neural network (recurrent neural networks,rnn)RNN has a fatal flaw, the traditional MLP also has this flaw, before looking at

http://www.deeplearningbook.org/The 6th Chapter Deep Feedforward NetworksDeep Feedforward Networks is also known as feedforward neural Networks or multi-layer perceptrons (MLPs), which is a very important depth learning model. The goal of

convolutional Neural Network is the first multi-layered neural network structure which has been successfully trained, and has strong fault tolerance, self-learning and parallel processing ability.First, the basic principle1.CNN algorithm

%2015.04.26 Kang yongxin----v 2% completion of the operation of the BP algorithm, the batch method to update the weight%%% input data format%x Matrix: Sample number * Feature dimension%y Matrix: Number of Samples * category number (in 01000 form)

BP (back propagation) neural network was proposed by the team of scientists led by Rumelhart and McCelland in 1986, which is one of the most widely used neural network models, which is a multilayer Feedforward network trained by error inverse

Transferred from: http://dataunion.org/11692.htmlZhang YushiSince July this year, has been in the laboratory responsible for convolutional neural networks (convolutional neural network,cnn), during the configuration and use of Theano and

We know that the perceptron is the simplest neural network, with only one layer. Perceptron is a machine that simulates the behavior of biological neurons. So this time to teach you how to use Python to implement the Perceptron, the model is as

[ML] My Journal from the neural Network to the deep learning:a Brief Introduction to the deep learning. Part. Eightdropout & MaxoutThis is the 8th post of a series of posts I planned about a journal of myself studying deep learning in Professor Bhik

SummaryThis section will take a visual understanding of the reverse propagation . Reverse propagation is a method of calculating the gradient of an expression recursively using the chain rule . Understanding the reverse propagation process and its

This is a 06 year old article, but a lot of places are worth looking at.I. SummaryThe main points of CNN's Feedforward Pass and BackPropagation Pass, the key is the convolution layer and polling layer of the BP deduction explained.Two, the classical

Paper notes "Maxout Networks" && "Network in Network"Posted in 2014-09-22 | 1 ReviewsSourceMaxout:http://arxiv.org/pdf/1302.4389v4.pdfnin:http://arxiv.org/abs/1312.4400ReferenceMaxout and NIN specific content without explanation, you can refer

TensorFlow is used to train a simple binary classification neural network model. Use TensorFlow to implement the 4.7 pattern classification exercise in neural networks and machine learning The specific problem is to classify the dual-Crescent

Original articleReprint please register source HTTP://BLOG.CSDN.NET/TOSTQ the previous section we introduce the forward propagation process of convolutional neural networks, this section focuses on the reverse propagation process, which reflects the

It mainly involves data migration of products, members, and orders, especially the data migration of members. Preliminary work: 1. Install standard ecstore2.3 (after secondary development, you need to compare whether it affects data

Principles of training multi-layer neural network using backpropagation The project describes teaching process of multi-layer neural network employing backpropagation algorithm. To illustrate this process, the three layer neural

For the principle of self-encoder, please refer to the blog http://blog.csdn.net/xukaiwen_2016/article/details/70767518, for its familiarity with the principle can be directly read the following code.The first is to use the relevant library,