Sparse coding

Sparse coding is a technique used in machine learning and neuroscience where data is represented using a small number of active features or elements. Imagine trying to recognize a face: instead of storing all the details, our brain focuses on key features like the eyes, nose, and mouth. In sparse coding, each piece of information is represented by a few important components, allowing for efficient storage and processing. This method captures the essential patterns in data while ignoring less important details, making it useful in tasks like image processing, speech recognition, and understanding complex datasets.