neural agility

BP (Back Propagation)The network was proposed by a team of scientists headed by Rumelhart and mccelland in 1986. It is a multi-layer feed-forward Network trained by the error inverse propagation algorithm and is one of the most widely used neural network models. The BP network can learn and store a large number of input-output mode ing relationships without revealing the mathematical equations that describe this ing relationship beforehand. The struct

1. Neural networksRoughly speaking, a neural network is a set of connected input/output units. Each connection is associated with a weight. In the learning phase, by adjusting these weights, we can predict the correct class labels of input tuples for learning. Due to the connection between units, neural network learning is also called connectionist learning ).

Neural networks have been very hot, there has been a period of depression, now because of deep learning reasons to continue to fire up. There are many kinds of neural networks: forward transmission network, reverse transmission network, recurrent neural network, convolution neural network and so on. This paper introduc

TensorFlow implements RNN Recurrent Neural Network, tensorflowrnn RNN (recurrent neural Network) recurrent neural Network It is mainly used for natural language processing (NLP) RNN is mainly usedProcess and predict sequence data RNN is widely used in speech recognition, language model, and machine translation. The source of RNN isDepicts the current output of a

The foundation of deep learning--the beginning of neural network Original address fundamentals of Deep learning–starting with Artificial neural network preface Deep learning and neural networks are now driving advances in computer science, both of which have a strong ability to learn from data and the environment, which also leads them to be the preferred tool i

Introduction of artificial neural network and single-layer network implementation of and Operation--aforge.net Framework use (v)The previous 4 article is about the fuzzy system, it is different from the traditional value logic, the theoretical basis is fuzzy mathematics, so some friends looking a little confused, if interested in suggesting reference related books, I recommend the "Fuzzy Math Tutorial", the defense industry Press, speaking very full,

**************************************Note: This blog series is for bloggers to learn the "machine learning" course notes from Professor Andrew Ng of Stanford University. Bloggers deeply learned the course, do not summarize is easy to forget, according to the course plus their own to do not understand the problem of the addition of this series of blogs. This blog series includes linear regression, logistic regression, neural network, machine learning

first, the Origin Originally wanted to follow the traditional recursive algorithm to achieve maze game--> genetic algorithm to achieve maze game--> neural network maze game ideas, in this article also write how to use the neural network to achieve the maze, but the study, feel some trouble is not very good, so I chose the more common way, Realization of handwritten digit recognition (so-called mnist). intr

"Recurrent convolutional neural Networks for Text classification" Paper Source: Lai, S., Xu, L., Liu, K., Zhao, J. (2015, January). Recurrent convolutional neural Networks for Text classification. In Aaai (vol. 333, pp. 2267-2273). Original link: http://blog.csdn.net/rxt2012kc/article/details/73742362 1. Abstract Text categorization is an important foundational task for NLP. Traditional text categorizati

Article reproduced from: http://www.52analysis.com/R/1627.html Neural Network (optimization algorithm) Artificial neural Network (ANN), referred to as neural network, is a mathematical model or computational model that mimics the structure and function of a biological neural network.

gap. In the comprehensive evaluation of customer service perception of information system, it involves a lot of complex phenomena and the interaction of many factors, moreover, there are a lot of fuzzy phenomena and fuzzy concepts in the evaluation. Therefore, in the comprehensive evaluation, some scholars use the method of fuzzy comprehensive evaluation to quantify, evaluate the information System customer service awareness level, and has achieved some results. However, using this method to mo

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 classification, image positioning and image de

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 neural