Applications of Calculus in Artificial Intelligence and Machine Learning Training Models
Authors/Creators
- 1. Assistant Professor, Department of Mathematics, Radhabai Kale Mahila Mahavidyalaya Ahilyanagar
Description
Artificial Intelligence (AI) has now become one of the most disruptive technologies of the century. Numerous fields in mathematics are useful in AI, such as linear algebra, probability, statistics, and calculus. Of them, calculus is a core part of machine learning algorithm design and optimization. Derivatives, gradients, partial derivatives, integrals and optimization methods are some of the concepts that are used in training models and enhancing performance of predictive models. This paper will discuss the main uses of calculus in artificial intelligence with a special focus on optimization, neural networks, gradient descent algorithms, deep learning, and probabilistic models. An example is also provided in Python to show how calculus-based optimization makes machine learning models better. The paper provides significant insights into the use of calculus as the basis of the contemporary AI frameworks.
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12. Mahesh Ramesh Aware.pdf
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Additional details
References
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