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Academic Discipline

Mathematics

Linear algebra, real and complex analysis, topology, differential geometry, probability, combinatorics, and number theory.

18courses·132standalone talks·432total lectures

Subfields

All Mathematics432 Calculus & Analysis164 Linear Algebra107 Category Theory, Topos Theory & Set Foundations60 Topology & Geometry59 Probability & Information Theory39 Combinatorics & Graph Theory34 Control & Dynamical Systems31 Convex Optimization21 Formal Methods & Type Theory21 Number Theory & Abstract Algebra18 Statistical Learning & Causality7 Algorithmic Information & Coding Theory5 Cryptography4 Computational Complexity3

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Shannon's Channel and Capacity: A Mystery in Three Acts

Shannon's Channel and Capacity: A Mystery in Three Acts

Mathematics·Research Seminar·Topology & Geometry · Michelle Effros · Caltech

Michelle Effros

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37:22

Multiplying and Factoring Matrices

Multiplying and Factoring Matrices

Matrix Methods in Data Analysis, Signal Processing, and Machine Learning · Lec 2·Gaussian Elimination & Matrix Systems · Gilbert Strang · MIT

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48:25

Four Ways to Solve Least Squares Problems

Four Ways to Solve Least Squares Problems

Matrix Methods in Data Analysis, Signal Processing, and Machine Learning · Lec 9·Linear Algebra · Gilbert Strang · MIT

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49:51

Orthonormal Columns in Q Give Q'Q = I

Orthonormal Columns in Q Give Q'Q = I

Matrix Methods in Data Analysis, Signal Processing, and Machine Learning · Lec 3·Convex Optimization · Gilbert Strang · MIT

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49:24

Positive Definite and Semidefinite Matrices

Positive Definite and Semidefinite Matrices

Matrix Methods in Data Analysis, Signal Processing, and Machine Learning · Lec 5·Convex Optimization · Gilbert Strang · MIT

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45:27

Eckart-Young: The Closest Rank k Matrix to A

Eckart-Young: The Closest Rank k Matrix to A

Matrix Methods in Data Analysis, Signal Processing, and Machine Learning · Lec 7·Singular Value Decomposition (SVD) · Gilbert Strang · MIT

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47:16

Minimizing "x" Subject to Ax = b

Minimizing "x" Subject to Ax = b

Matrix Methods in Data Analysis, Signal Processing, and Machine Learning · Lec 11·Convex Optimization · Gilbert Strang · MIT

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50:22

Derivatives of Inverse and Singular Values

Derivatives of Inverse and Singular Values

Matrix Methods in Data Analysis, Signal Processing, and Machine Learning · Lec 16·Signal Processing & Circuit Analysis · Gilbert Strang · MIT

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43:08

Showing 8 of 8 lectures·6.2h shown

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Systems & CS (434)Physics & Cosmology (413)AI & Machine Learning (213)History & Humanities (376)Philosophy & Ethics (264)Biology & Neuroscience (281)Economics & Finance (336)Algorithms & Theory (339)Engineering & Robotics (209)

Signal Processing & Circuit Analysis · Signal Processing & Robotics

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