Neural Network Genetic Algorithm/Programming
Design a and program neural network which is optimised with genetic algorithm / genetic programming (written in C++ or python language). The weights of the neural network are to be determined by the genetic algorithm .genetic programming rather than the traditional method of trial and error. The aim here is to improve the time it takes to determine the appropriate weights for learning a particular task. The task itself is not important. For example, for the task of image recognition, e.g. recognising images of cars, the genetic algorithm/programming should take a shorter time determining the appropriate weights /Inputs into the network.
Also, the structure of the neural network should also be determined using the same method (GA/GP). That is, the number of layers and number of nodes within the network. Please provide references when citing other works for comparison, clarification etc.
Hello.
I read your requirement.
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Hello
Please look at my portfolio, you will see Im developing an application dedicated exclusively to Artificial Intelligence, specially Neural Networks, I would like you to message me to discuss your needs and give you my opinions about it.
Best regards
Edixon Vargas.
I can get the job done as per your requirements since I have some experience of working with neural networks and had implemented Probabilistic Neural Networks for a course project in recent year. If given chance, I can get the work done for you with quality and reliability.
Thanks,
hello,
I am computer graduate with two year of experience. I also scored corporate gold medal in advance data warehouse techniques. In this course we worked on different algorithms in which neural network was also included. I know the algorithm and can implement into code. I will fulfill all your requirements.
waiting for your positive response.
for further detail please inbox me.
Hello
Recent CS graduate from IIT Bombay. Previously a research assistant, having worked on the problem of OCR using attention-based deep learning and memory augmented neural networks.
Just saying, the first requirement - evolution using genetic algorithm to reach the optimal set of weights is doable. However, the second requirement, i.e. finding the optimal set of layers and nodes is akin to hyperparameter optimization which might take much, much more time and juice. The current price range doesn't justify the requirements.
Can help you with first part and to some extent the second part. New freelancer here. Ping me if interested.
Regards
Aditya