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20. Definitions and Inequalities
Автор: MIT OpenCourseWare
Загружено: 2019-05-16
Просмотров: 29943
Описание:
MIT 18.065 Matrix Methods in Data Analysis, Signal Processing, and Machine Learning, Spring 2018
Instructor: Gilbert Strang
View the complete course: https://ocw.mit.edu/18-065S18
YouTube Playlist: • MIT 18.065 Matrix Methods in Data Analysis...
This lecture continues the focus on probability, which is critical for working with large sets of data. Topics include sample mean, expected mean, sample variance, covariance matrices, Chebyshev's inequality, and Markov's inequality.
License: Creative Commons BY-NC-SA
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