Neural networks, lauded for their skill to analyze complex data, have become a cornerstone of modern machine learning. However, their intricate structure often remains as a mystery, leading to the proverbial "black box" {phenomenon|. For those seeking to understand the inner mechanisms of these p

Neural networks, the complex 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 framework and the process of training. We