<ul data-eligibleForWebStory="true"><li>Neural Networks are inspired by the minute cells in our heads called neurons, enabling advancements like face recognition and self-driving cars.</li><li>Neural Networks consist of layers of small decision-making units known as neurons, which process information and learn patterns over time.</li><li>These networks work by taking in data like images or sounds, making simple decisions at each layer, and eventually recognizing patterns.</li><li>For example, in recognizing cats in photos, the network analyzes numbers representing colors and brightness, identifying features like ears, whiskers, and fur.</li><li>The network iterates through multiple layers, refining its guesses and ultimately making a decision on whether an image contains a cat.</li><li>Neural Networks continuously improve by learning from their mistakes, adjusting attention to different cues, similar to studying harder after getting quiz questions wrong.</li><li>They are omnipresent, enhancing apps and devices by making them smarter and faster at interpreting information.</li><li></li></ul>

Neural Networks Explained in 3 Minutes

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