Am I going in the right direction?

I am currently creating a neural network.
I know it's going to be a tough goal for a beginner like me, but I honestly don't have anything else that actually motivates me to make. Also, I really do want to make it in C++ because I am NOT in the mood to learn python or any other language right now.

The desired objective of my neural network is to simply do this (in coding terms):
#include <iostream>

int x = 1; //any positive single-digit
int y = 2; //any positive single-digit

if (x == y){
std::cout << "True" << std::endl;
std::cout << "False" << std::endl;

Of course the neural network won't actually print "True" but it will output
either 0 or 1 for true or not.
However, after working on it for the past few days I am wondering if I am going in the right direction with this.

Actually, I'll break it down.

I am currently using inheritance to create my Neuron classes.

The network is as such:
2 inputs
3 hidden layers
1 output

I am using this for training my neural network:

And I would like to know what tips you could give me for it.

(1)What should I use to hold 'neurons', arrays or vectors?
(2)What should I do to train, Back propagation or another easier to understand technique to train algorithms that is as efficient and quick?
(3)Any other tips?

P.S. Unless it is beyond necessary, I don't want to drown myself in calculus. The video I linked actually explains it without calculus.

P.P.S Code can be provided if you so request.

P.P.P.S. Most of my code is unfinished, but I decided it was better to ask you guys then to continue.
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