Computational Complexity

Computational Complexity is the study of the resources required to solve computational problems. It is concerned with understanding the inherent difficulty of solving a problem and the amount of resources, such as time and memory, required to solve it. In Data Science and Artificial Intelligence, computational complexity is an important consideration when designing algorithms and models. It helps in determining the feasibility of solving a problem and the efficiency of the solution. The complexity of a problem is often measured in terms of time complexity and space complexity, which refer to the amount of time and memory required to solve the problem, respectively. The study of computational complexity has led to the development of various complexity classes, such as P, NP, and NP-complete, which are used to classify problems based on their difficulty and the resources required to solve them.
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