neural agility

Awesome Recurrent neural NetworksA curated list of resources dedicated to recurrent neural networks (closely related to deep learning).Maintainers-jiwon Kim, Myungsub ChoiWe have pages for other topics:awesome-deep-vision, awesome-random-forestContributingPlease feel free-to-pull requests, email myungsub Choi ([e-Mail protected]) or join our chats to add links.Sharing Share on Twitter Share on

Learning is one of the most important and compelling features of neural networks. In the development process of neural network, the study of learning algorithm has a very important position. At present, the neural network model proposed by people is corresponding to the learning algorithm. So, sometimes people don't ask for a strict definition or distinction betw

Label: style blog HTTP Io SP strong on 2014 Preface: Keep your style consistent. Before you officially start writing, start with a long talk. There are too many books and articles about neural networks, so I am not allowed to talk about them in a word that is too arrogant. I try to write a little more information. After reading this article, I can have a general understanding of neural networks and have so

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 development of neural networks has gone through 3 stages: 1947-1969 years early, during which tim

The original book: "AI Technology in Game programming" Excerpt from: http://blog.csdn.net/starxu85/article/details/3143533 Original: http://blog.csdn.net/zzwu/article/category/243067 . (one of the serials) introduce neural networks in normal language(neural Networks in Plain 中文版) Because we don't have a good understanding of the brain, we often try to use the latest technology as a model to exp

Order: This series is based on the neuralnetwork and deep learning book, and I have written my own insights. I wrote this series for the first time. What's wrong! Next, we will introduce neural networks so that you can understand what neural networks are. For better learning, we will be guided by identification numbers later. Let's study it step by step! Let's talk about some of them first! Sometimes do you

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 to associate computer vision. CNNs has made gr

Original: https://medium.com/learning-new-stuff/how-to-learn-neural-networks-758b78f2736e#.ly5wpz44dThe second post in a series of me trying to learn something new over a short period of time. The first time consisted of learning how to does machine learning in a week.This time I ' ve tried to learn neural networks. While I didn ' t manage to does it within a week, due to various reasons, I did get a basic

This blog will introduce a neural network algorithm package in R: Neuralnet, which simulates a set of data, shows how it is used in R, and how it is trained and predicted. Before introducing Neuranet, let's briefly introduce the neural network algorithm .Artificial neural Network (ANN), or neural network, is a mathemat

Convolution Neural network Convnets is used to process data with multiple array formats, such as a color image consisting of three two-dimensional arrays, which contains pixel intensities on three color channels. Many data forms are in the form of multiple arrays: one-dimensional signals and sequences, including languages; Two-dimensional image or audio spectrum, three-dimensional video or stereo image. Convnets has four key ideas that take advantage

Recurrent neural NetworksIn traditional neural networks, the model does not focus on the processing of the last moment, what information can be used for the next moment, and each time will only focus on the current moment of processing. For example, we want to classify the events that occur at every moment in a movie, and if we know the event information in front of the movie, then it is very easy to classi

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