The rapid development of Artificial Intelligence (AI), has made a clear understanding of the mathematics behind it essential. This post breaks down the complicated mathematics required to understand AI.
The objective of this blog post is to explain the various mathematical concepts that are fundamental to the understanding and development of AI.
The Role of Basic Mathematics in AI
A strong foundation in basic mathematics is crucial for learning AI. Mathematical logic, functions, relations and sets constitute the basis of these concepts.
Need for Algebra in AI
Algebra allows one to formalize the way we play with numbers and construct mathematical structures. In AI, it comes handy in coding algorithms efficiently.
Understanding Probability and Statistics in AI
Probability and statistics are used in AI to model the randomness and uncertainty that often occur in the real world. They are especially crucial for machine learning algorithms.
Calculus in AI
Calculus, including partial differential equations and optimization, is used to maximize or minimize error rates, while building neural networks. It is also essential in real-time decision making.
Linear Algebra in AI
Linear algebra is the branch of mathematics describing linear equations. In AI, it’s used to handle images, speech recognition, natural language processing and everything involving arrangement in 2D, 3D or even higher dimensions.
