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Artificial neural network

Artificial neural network
An artificial neural network is an interconnected group of nodes, akin to the vast network of neurons in a brain. Here, each circular node represents an artificial neuron and an arrow represents a connection from the output of one neuron to the input of another. For example, a neural network for handwriting recognition is defined by a set of input neurons which may be activated by the pixels of an input image. After being weighted and transformed by a function (determined by the network's designer), the activations of these neurons are then passed on to other neurons. This process is repeated until finally, an output neuron is activated. This determines which character was read. Like other machine learning methods - systems that learn from data - neural networks have been used to solve a wide variety of tasks that are hard to solve using ordinary rule-based programming, including computer vision and speech recognition. Background[edit] History[edit] Farley and Wesley A. Models[edit] or both

http://en.wikipedia.org/wiki/Artificial_neural_network

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What is neural network? - Definition from Whatis In information technology, a neural network is a system of programs and data structures that approximates the operation of the human brain. A neural network usually involves a large number of processors operating in parallel, each with its own small sphere of knowledge and access to data in its local memory. Typically, a neural network is initially "trained" or fed large amounts of data and rules about data relationships (for example, "A grandfather is older than a person's father"). A program can then tell the network how to behave in response to an external stimulus (for example, to input from a computer user who is interacting with the network) or can initiate activity on its own (within the limits of its access to the external world). In making determinations, neural networks use several principles, including gradient-based training, fuzzy logic, genetic algorithms, and Bayesian methods. Contributor(s): Lee Giles

Neural Network Toolbox - MATLAB - MathWorks France Neural Network Toolbox™ provides functions and apps for modeling complex nonlinear systems that are not easily modeled with a closed-form equation. Neural Network Toolbox supports supervised learning with feedforward, radial basis, and dynamic networks. It also supports unsupervised learning with self-organizing maps and competitive layers. With the toolbox you can design, train, visualize, and simulate neural networks. You can use Neural Network Toolbox for applications such as data fitting, pattern recognition, clustering, time-series prediction, and dynamic system modeling and control. To speed up training and handle large data sets, you can distribute computations and data across multicore processors, GPUs, and computer clusters using Parallel Computing Toolbox™.

Artificial Intelligence Marketing Artificial intelligence marketing (AIM) is a form of direct marketing leveraging database marketing techniques as well as AI concept and model such as machine learning and Bayesian Network. The main difference resides in the reasoning part which suggests it is performed by computer and algorithm instead of human. Behavioral targeting[edit] Open Source: the Meritocracy vs the Circle of Trust There has been this idea running around the back of my head for a while, and it's only now that it is starting to crystalize into something that I can express. When we look at Open Source projects, we see that there is a hierarchy of involvement. There are different levels at which you can be involved, and at each higher level, there will be less and less individuals. For now I am going to divide involvement up like this: Different Open Source projects but different barriers at different points. For example: (Note: I'm not going to even try and pretend that the above is a complete list of road-blocks)

Bioengineers Build Open Source Language for Programming Cells Drew Endy wants to build a programming language for the body. Endy is the co-director of the International Open Facility Advancing Biotechnology — BIOFAB, for short — where he’s part of a team that’s developing a language that will use genetic data to actually program biological cells. That may seem like the stuff of science fiction, but the project is already underway, and the team intends to open source the language, so that other scientists can use it and modify it and perfect it. The effort is part of a sweeping movement to grab hold of our genetic data and directly improve the way our bodies behave — a process known as bioengineering. With the Supreme Court exploring whether genes can be patented, the bioengineering world is at crossroads, but scientists like Endy continue to push this technology forward.

Researchers Create Artificial Neural Network from DNA 5inShare Scientists at the California Institute of Technology (Caltech) have successfully created an artificial neural network using DNA molecules that is capable of brain-like behavior. Hailing it as a “major step toward creating artificial intelligence,” the scientists report that, similar to a brain, the network can retrieve memories based on incomplete patterns. Potential applications of such artificially intelligent biochemical networks with decision-making skills include medicine and biological research. The researchers predict that, eventually, neural networks could be developed that operate within cells to gather information for disease diagnosis. More details from Caltech:

【面向代码】学习 Deep Learning(三)Convolution Neural Network(CNN) - DarkScope从这里开始 最近一直在看Deep Learning,各类博客、论文看得不少 但是说实话,这样做有些疏于实现,一来呢自己的电脑也不是很好,二来呢我目前也没能力自己去写一个toolbox 只是跟着Andrew Ng的UFLDL tutorial 写了些已有框架的代码(这部分的代码见github) 后来发现了一个matlab的Deep Learning的toolbox,发现其代码很简单,感觉比较适合用来学习算法 Robots and Avatars Documentation: Pathways | Gallery | Video | Vodcasts | Reports Robots and Avatars have produced a series of vodcasts which are available to view on this site. They explore the themes of the programme, including Artifical Intelligence, Behaviours and Ethics, Health and Wellbeing and the Future Workplace from the perspective of a diverse array of professionals and experts who share their thoughts and insights in this series of interviews. Click here to view Vimeo channel or watch videos below.

10 open source e-learning projects to watch - Collaboration - Open Source As corporate and government organizations embrace the Web for delivering more education and training programs, a wealth of free and open source e-learning applications will help lower the barrier to entry. TechWorld looks at the options. ATutor ATutor is a Web-based learning content management system (LCMS) designed for accessibility and adaptability by the Adaptive Technology Resource Centre at the University of Toronto.

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