Hey guys I'm in an "advanced" programming course at a community college and one of the semester projects we can do is some kind of AI. Problem is I haven't taken statistics or linear algebra yet. I do have a book on data science but I haven't read it yet and I don't have time during the semester. I was thinking of using a genetic Algorithm rather than some kind of crazy efficient neural network that I would have no idea how to do. I got into CS because I wanted to work with AI and bioinformatics so I think now is a good time to do my first AI. Should I do a genetic Algorithm or just do some other project? Idk I'm indisicive idk to do
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Do you know calculus? Because as far as training ANNs you just need to know derivatives, and the two derivatives that matter are sigmoid and hyperbolic tangent, both of which are on google.
Genetic algorithms are also good, although will take longer to complete. However, easy to write, GAs are usually better when you have no idea what the outcome is supposed to be, but you know when you're there.
BackProp is better when you know what you're trying to classify.
If you want to do one or the other, do both. GA and ANN training work together very well.
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Well you said you wanted to do AI, and ANNs are the basics of AI.
And you can indeed use GAs to do it.
If you can't do neural networks yet, then you don't want to do an AI project, instead focusing on GA instead, or any of the Evolutionary algorithms if you'd like, GAs, particle/swarm, simulated annealing, etc.
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(a sidenote, not really disagreeing)
well, ANN’s are the current rage, no doubt about it. and they get interesting results, when combined in certain ways or layers. but in essence they are still feedback systems that calibrate themselves using error difference feedback based on training data. so ”AI” is a big word to use.
if you strip all the gobblygook, the algorithm is essentially a multilayered error minimizing gradient descent.
I’m kinda hoping someone finds a way to create algorithm that configures the ANN layering and connections based on error deltas, and maybe by nerve cluster (or even creating new clusters). that would be quite interesting :)
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My point was only that it's a basis of it, not that it is it. OP has done neither, so my only suggestion was combine both GAs and ANNs together so OP could experience both.
That's all I was saying with that. Someone with zero experience is not going to just create general AI out of thin air.
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