Neural Network Training

Kyle explains the two phases of training a neural network: forward propagation and backpropagation. He emphasizes the importance of adjusting weights based on error gradients to reach a refined solution, while also discussing the risks of overfitting and the need for careful tweaking in machine learning algorithms.