Mathematics for Machine Learning Tutorial (3 Complete Courses in 1 video)

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Mary
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몇 초 만에 비디오를 돋보이게 만드세요. 음성, 언어, 스타일, 대상 관객을 원하는 대로 조정하세요!
요약
The course covers mathematical foundations for machine learning, focusing on linear algebra and multivariate calculus. Topics include eigenvalues, eigenvectors, optimization, and principal component analysis (PCA). Students learn to fit functions to data, derive PCA, and understand concepts like Jacobians and Hessians, ultimately applying these tools for dimensionality reduction and data analysis.
자막
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