Random Initialization, Deep Learning.
problem. Each neuron gets a unique starting point, allowing them to learn different features and contribute diversely to the network’s output. This is crucial for capturing the complexities of real-world data. The solution to this is to initialize your parameters randomly. So here’s what you do.