Applications Of Numerical Techniques in Machine Learning and Artificial Intelligence

Artificial Intelligence (AI) is one of the newest technologies that have become a key driver of modern computing and is used in image recognition, natural language processing, autonomous vehicles, and healthcare analytics. These intelligent systems are backed up by a solid mathematical basis especially by numerical techniques. Numerical Methods give efficient procedures in solving mathematical problems that are not solvable analytically or they demand approximations of computation. They are important in the training of machine learning models, algorithm optimization, solving of DEs, and the processing of large data volumes. This paper will discuss the uses and purposes of numerical methods in artificial intelligence, such as optimization, matrix computations, root-finding methods, numerical differentiation and numerical integration. The paper emphasizes the role of numerical algorithms to improve the efficiency and accuracy of AI systems and explains the uses of the tool in the fields of neural networks, computer vision, and predictive analytics.