I have a specific problem of having to decide in a fuzzy way between various outputs from a given set of metrics. It's a perfect candidate for neural network approaches.
I've used Joone in the past with success but I'm a little scared of its 2MB jar file for something that in my mind can be done in far less code than that.
Of course t...

I was discussing neural networks (NN) with a friend over lunch the other day and he claimed the the performance of a NN written in Java would be similar to one written in C++. I know that with 'just in time' compiler techniques Java can do very well, but somehow I just don't buy it. Does anyone have any experience that would shed light...

Hi.
Any good tutorial with source that will demonstrate how to develop neural network (step bay step for dummies ;-))
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I will be entering my third year of university in my next academic year, once I've finished my placement year as a web developer, and I would like to hear some opinions on the two modules in the Title.
I'm interested in both, however I want to pick one that will be relevant to my career and that I can apply to systems I develop.
I'm do...

I am looking for good resources for AI programming (any language), both books and online stuff. I am particularly interested in neural networks implementations.
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I was having a look at this awesome tutorial on single layer perceptron. I tried the implementation out and it works like charm, but I was wondering if it's there any practical use for it as is (at such a low complexity degree).
Any example?
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I have a Probablistic Neural Network classification experiment set up in matlab. I can get the classes for unseen data using the sim command. Is there any way i can get the probabilities for the classes that the classifier calculates. Also is there any direct way to plot the Reciever Operating Characterstic curve and calculate the Area U...

I'm looking for computationally heavy tasks to implement with CUDA and wonder if neural networks or bayesian networks might apply. This is not my question, though, but rather what the relation between the two network types is. They seem very related, especially if you look at bayesian networks with a learning capability (which the articl...

I am not a mathematician. I enjoy a good math puzzle, but I admit my weaknesses whole heartedly. That said, I've always had an interest in Neural Networks, and while I understand them enough to implement them from scratch, I hit a wall when I need to understand any concept that I can only find mathematic proofs for. Where is the programm...

As I learn more about Computer Science, AI, and Neural Networks, I am continually amazed by the cool things a computer can do and learn. I've been fascinated by projects new and old, and I'm curios of the interesting projects/applications other SO users have run into.
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Welcome!
I very enjoyed programming artificial intelligence in my studies - neural networks, expert machines and other. But in work I develop mainly web applications.
And now I think about returning to such programming, maybe in hobby, or maybe in work. Are there areas where AI is commonly used in applications development and programme...

Generally speaking what do you get out of extending an artificial neural net by adding more nodes to a hidden layer or more hidden layers?
Does it allow for more precision in the mapping, or does it allow for more subtlety in the relationships it can identify, or something else?
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I've been trying to learn about Neural Networks for a while now, and I can understand some basic tutorials online, and I've been able to get through portions of Neural Computing - An Introduction but even there, I'm glazing over a lot of the math, and it becomes completely over my head after the first few chapters. Even then its the lea...

I've been profiling an application all day long and, having optimized a couple bits of code, I'm left with this on my todo list. It's the activation function for a neural network, which gets called over a 100 million times. According to dotTrace, it amounts to about 60% of the overall function time.
How would you optimize this?
pub...

Since a lot of these sites found on google use mathematical notation and I have no idea what any of it means I want to make a feedforward neural network like this:
n1
i1 n3
n2 o1
i2 n4
n3
Now can someone explain to me how to find the value of o1? How is it possible to make a neuron active when none of its...

I am currently building a Neural Network library. I have constructed it as an object graph for simplicity. I am wondering if anyone can quantify the performance benefits of going to an array based approach. What I have now works very good for building networks of close to arbitrary complexity. Regular (backpropped) networks as well as r...

I'm really interested in Neural nets, but I'm looking for a place to start.
What resources are out there and what is a good starting project(s)?
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SharpNEAT is a NeuroEvolution of Augmenting Topologies (NEAT) library in C#.
The whole thing sounds pretty exciting but I can't find a damn sample/tutorial anywhere!
Any help appreciated!
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When training a multi-layer neural network, using a sigmoidal activation function is necessary for it to learn efficiently.
Is there any advantage to using a sigmoidal activation function when training a single layer perceptron, or is a simple step (heaviside) function sufficient (or even preferable)?
I'm slowly getting my head around...

Hello..
I am wanting some expert guidance here on what the best approach is for me to solve a problem. I have investigated some machine learning, neural networks, and stuff like that. I've investigated weka, some sort of baesian solution.. R.. several different things. I'm not sure how to really proceed, though. Here's my problem.
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