Skip Connections

Skip connections are a technique in neural networks that allow information to bypass certain layers and be directly passed to later ones. Think of it like taking a shortcut on a road trip; instead of traveling through every stop, you skip some to reach your destination faster. This helps the network learn better by preserving important details and reducing problems like vanishing gradients, leading to improved accuracy, especially in complex tasks like image recognition or translation. Essentially, skip connections facilitate smoother information flow within the network, enabling more efficient and effective learning.