Neural networks, celebrated for their ability to analyze complex data, have become a foundation of modern machine learning. However, their complex structure often remains as a enigma, leading to the common "black box" {phenomenon|. For those desiring to comprehend the inner mechanisms of these powerful systems, a voyage into their core is crucial.

Neural networks, the sophisticated architectures of artificial intelligence, have advanced fields from autonomous driving. Yet, their decision-making processes remain a elusive black box. This article aims to shed light on these neural networks, exploring their structure and the process of training. We'll embark on the layers of a neural network, u