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"Neural Network and deep learning" article Three: sigmoid neurons

Source: Michael Nielsen's "Neural Network and Deep leraning", click the end of "read the original" To view the original English.This section translator: Hit Scir master Xu Wei (https://github.com/memeda)Statement: We will be in every Monday, Thursday, Sunday regularly serialized the Chinese translation of the book, if you need to reprint please contact [email protected], without authorization shall not be r

Refresh neural Network New depth: Imagenet Computer Vision Challenge Microsoft China researcher wins

Microsoft Research Asia chief researcher Sun JianHow accurate is the world's best computer vision system? On December 10 9 o'clock in the morning EST, the imagenet Computer Vision Recognition Challenge was announced--Microsoft Research Asia Vichier's researchers, with the latest breakthroughs in deep neural network technology, have won the title of all three major projects with absolute advantage in image c

Go Introduction and realization of BP artificial neural network

Neural network concepts and suitability fieldsThe earliest research of neural network was proposed by the 40 psychologist McCulloch and mathematician Pitts, and their MP model was the prelude of Neural Network research.The develop

Dropout principle of activating function of neural network batchnormalization code implementation

identity activation function (i.e. f (x) =x), this property is not satisfied, and if MLP is using an identity activation function, then the entire network is equivalent to a single-layer neural network. Micro-Usability: This property is necessary when the optimization method is based on the gradient. Monotonicity: Whe

Neural Network algorithm

1. Background:1.1 Inspired by neural networks in the human brain, there have been many different versions in history. 1.2 The most famous algorithms are the backpropagation of the 1980.2. Multilayer forward neural networks (multilayer feed-forward neural network)The 2.1 backpropagation is used on a multilayer forward

Linear neural network based on perceptron model _ AI

Summary: WithThe artificial neural network has been developed with the development of computational intelligence. The industry now considers that the classification of Neural Networks (NN) in artificial intelligence (AI) may not be appropriate, and that the classification of computational Intelligence (CI) is more descriptive of the problem. Some topics in evolut

An introduction to the convolution neural network for Deep Learning (2)

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 correlation algorithm for multi-layer

Learning algorithm of Ann training algorithm based on traditional neural network

Learning/Training Algorithm classification The different types of neural networks correspond to different kinds of training/learning algorithms. Therefore, according to the classification of neural networks, the traditional neural network learning algorithms can be divided into the following three categories: 1 feedfor

Practice of deep learning algorithm---convolution neural network (CNN) principle

this:According to our experience, if the alphabet can be moved to the center of the field of view, the difficulty of recognition will be reduced a lot, in favor of improving the recognition rate.In this case, if we can change the image to the standard size, we can increase the corresponding recognition rate.For objects of real knowledge, from different angles, there will be different manifestations, even for the letter recognition, the letter can appear rotating:If the image can be rotated, the

From Alexnet to Mobilenet, take you to the deep neural network

Summary:On March 13, 2018, the Shen Junan community, from Harbin Institute of Technology, shared a typical model-an introduction to deep neural networks. This paper introduces the development course of deep neural network in detail, and introduces the structure and characteristics of each stage model in detail.The Shen Junan of Harbin Institute of Technology shar

A course of recurrent neural Network (1)-RNN Introduction _RNN

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

Big Data era: a summary of knowledge points based on Microsoft Case Database Data Mining (Microsoft Neural Network analysis algorithm principle)

Reprint: http://www.cnblogs.com/zhijianliutang/p/4050931.htmlObjectiveThis article continues our Microsoft Mining Series algorithm Summary, the previous articles have been related to the main algorithm to do a detailed introduction, I for the convenience of display, specially organized a directory outline: Big Data era: Easy to learn Microsoft Data Mining algorithm summary serial, interested children shoes can be viewed, Before starting the Microsoft Neural

Neural network and deep Learning notes (1)

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

Basic methods and practical techniques used in the design of BP neural network

Although the research and application of neural network has been very successful, but in the development and design of the network, there is still no perfect theory to guide the application of the main design method is to fully understand the problem to be solved on the basis of a combination of experience and temptation, through a number of improved test, finall

Deep learning "engine" contention: GPU acceleration or a proprietary neural network chip?

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

Torch Getting Started note 10: How to build torch neural network model

This chapter does not involve too many neural network principles, but focuses on how to use the Torch7 neural networkFirst require (equivalent to the C language include) NN packet, the packet is a dependency of the neural network, remember to add ";" at the end of the statem

Convolution neural network Combat (Visualization section)--using Keras to identify cats

Original page: Visualizing parts of convolutional neural Networks using Keras and CatsTranslation: convolutional neural network Combat (Visualization section)--using Keras to identify cats It is well known, that convolutional neural networks (CNNs or Convnets) has been the source of many major breakthroughs in The fiel

Introduction to Artificial neural network (4)--aforge. NET Introduction

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

Technology to: Read the convolutional neural network in one article CNN

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 Cuda-convnet, Cuda-convnet2. In order to enhance the understanding and use of CNN, this blog post, in order to communicate with

Application of CNN convolutional Neural network in natural language processing

Absrtact: As the core technology of most computer vision system, CNN has made great contribution in the field of image classification. Starting from the use case of computer vision, this paper introduces CNN and its advantages in natural language processing and its function.When we hear convolutional neural networks (convolutional neural Network, CNNs), we tend t

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