Read "Genetic Algorithms + Neural Networks = Best of Both Worlds", source: https://towardsdatascience.com/gas-and-nns-6a41f1e8146d

see:

https://www.youtube.com/watch?v=I2heTejQP58&list=PLea0WJq13cnARQILcbHUPINYLy1lOSmjH&index=1

https://www.youtube.com/watch?v=XJ7HLz9VYz0&list=PLRqwX-V7Uu6Y7MdSCaIfsxc561QI0U0Tb

read chapter 7 of

https://www.cheshireeng.com/Neuralyst/doc/NUG14x.pdf

the above will explain how genetic algorithms can be used to choose optimum neural network configurations.

if you have excel 2003 or earlier down load Neuralyst demo and use it to study Neural Networks.

https://www.cheshireeng.com/Neuralyst/

Or program it yourself here

https://www.youtube.com/watch?v=1XkjVl-j8MM

https://www.youtube.com/watch?v=_tMpeah8XGQ

https://www.youtube.com/watch?v=4aksMtJHWEQ

https://www.youtube.com/watch?v=zqoNVjgJqqE

Dear Mr. Shah,

We have a number of publications in this field particularly in terms of the new Econophysics Field and Phynance Fields and Network Physics Interdisciplinary Field. These fields also overlap with String Theory and Field Theories and Mathematical Physics and also Computer Science. You can take a look at our publications in terms of solution to P vs. NP problem with ECommerce Network Field and Externetwork Field and Quantum Mechanics on www.researchgate.net/profile/Soumitra_Mallick. It is partly based on a paper presented at the ICFAI International Conference held in Ahmedabad. This was the first time I got the opportunity to visit Mahatma Gandhi's Sabarmati Ashrama which was like a pilgrimage. Best wishes on your endeavours.

Earl Soumitra K. Mallick(Corresponding author), Director Somak Raychaudhury, Earl Prince Sandipan Mallick, and others

Calcutta University, IUCAA, IIT(BHU), respectively

and RHMHM School USA, Japan, Russia, India

and other respective affiliations.

Hello D. Shah ,

This chapter by Michael Nielsen is a very good place to learn about neural network and back propagation:

http://neuralnetworksanddeeplearning.com/chap2.html

Regarding Genetic algorithm and neural networks, I found these articles helpful:

1. https://towardsdatascience.com/gas-and-nns-6a41f1e8146d

2. https://towardsdatascience.com/artificial-neural-networks-optimization-using-genetic-algorithm-with-python-1fe8ed17733e

3. https://blog.coast.ai/lets-evolve-a-neural-network-with-a-genetic-algorithm-code-included-8809bece164

I can tell you the resources:

genetic algorithm: there is good lecture by MIT prof patrick j winston on youtube. There is a video by a channel two minute papers on GE.

for understanding of neural network - Go to 3blue1brown channel on YouTube that would be enough.

For Backpropagation: Read the papers from the makers of back prop Geoffrey hinton

The simple and clear source with a lot of examples is the book :

Artificial Intelligence "A guide to intelligent systems". Mıchael NEGNEVITSKY

As you can take a look at the e-book from Pact for the author : Dennis ROTHMAN

" Artificial Intelligence By Example"