Modularity
Modularity refers to the degree to which a system or a process is composed of separate components that can be connected, combined, and rearranged in various ways. In data science and artificial intelligence, modularity is an important concept that allows for the creation of complex systems by breaking them down into smaller, more manageable parts. This approach enables developers to build systems that are easier to understand, test, and maintain. Modularity is also essential for scalability, as it allows for the addition or removal of components without affecting the entire system. In machine learning, modularity is often achieved through the use of modular neural networks, which consist of multiple interconnected modules that can be trained separately and combined to form a larger network. Overall, modularity is a key principle in data science and artificial intelligence that enables the creation of flexible, scalable, and maintainable systems.
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