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Mathematics for Machine Learning
د.إ 25
Mathematics for Machine Learning by Marc Deisenroth is a foundational book that introduces the essential mathematical concepts needed for understanding machine learning. The book covers topics such as linear algebra, probability, optimization, and calculus, all of which are crucial for building machine learning models. It’s designed to make these mathematical concepts accessible to readers who may not have a strong background in math, while also offering enough depth for those looking to strengthen their understanding. Through clear explanations and practical examples, the book prepares readers to tackle more advanced machine-learning techniques and algorithms.
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