Neural Networks are like a group of very smart friends who work together to solve a problem. Each friend is good at understanding a small part of the problem, and when they combine their knowledge, they can figure out really complex things.
Think of it this way: Imagine you’re trying to solve a big jigsaw puzzle. Each piece of the puzzle is like a bit of information. You and your friends each take some pieces and work on putting them together. Some friends focus on the edges, others on the colors, and others on the shapes. As you all work together and share what you’ve found, the whole picture starts to come together.
In a neural network, each “friend” is like a tiny brain cell, called a neuron. These neurons are organized in layers. The first layer takes in the raw information (like the pieces of the puzzle), and each subsequent layer processes this information a bit more, passing it along to the next layer. By the time the information reaches the last layer, the neural network has put all the pieces together to understand the full picture.
So, in simple terms, neural networks are a way for computers to solve complex problems by breaking them down into smaller, manageable pieces and having lots of tiny “brain cells” work together to figure things out.
