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
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
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
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
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
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
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/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
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
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
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
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 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
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 (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
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
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
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
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
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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