Neural networks, lauded for their capacity to process complex data, have become a foundation of modern machine learning. However, their intricate structure often persists as a enigma, leading to the familiar "black box" {phenomenon|. For those aiming to grasp the inner operations of these powerful systems, a exploration into their depths is crucial

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