Niebles and Ranjay Krishna Stanford Vision and Learning Lab 10217 1 Another very indepth linear algebra review from CS229 is available here httpcs229stanfordedusectioncs229linalgpdf ID: 656155 Download Presentation

Alexander G. Ororbia II. The Pennsylvania State University. IST 597: Foundations of Deep Learning. About this chapter. Not a comprehensive survey of all of linear algebra. Focused on the subset most relevant to deep learning.

Calculus Functions of single variable Limit con tinuity and differentiability Mean value theorems Evaluation of definite and improper integrals Partial derivatives Total derivative Maxima and minima Gradient Divergence and Curl Vector identities Di

Calculus Functions of single variable Limit continuity and differentiability Mean value theorems Evaluation of definite and improper integrals Partial derivatives Total derivative Maxima and minima Gradient Divergence and Cu rl Vector identities Di

Calculus Functions of single variable Limit con tinuity and differentiability Mean value theorems Evaluation of definite and improper integrals Partial derivatives Total derivative Maxima and minima Gradient Divergence and Cu rl Vector identities D

Calculus Mean value theorems Theorems of integral calculus Evaluation of definite and improper integrals Partial Derivatives Maxima and minima Multiple integrals Fourier series Vector identities Directional derivatives Line Surface and Volume integ

Calculus Mean value theorems Theorems of integral calculus Evaluation of definite and improper integrals Partial Derivatives Maxima and mini ma Multiple integrals Fourier series Vector identities Directional derivatives Line Surface and Volume integ

Calculus Functions of single variable limit continuity and differentiability mean value theorems evaluation of definite and improper integrals partia l derivatives total derivative maxima and minima gradient divergence and curl vector identities dir

Calculus Mean value theorems Theorems of integral calculus Evaluation of definite and improper integrals Partial Derivatives Maxima and minima Multiple integrals Fourier series Vector identities Directional derivatives Line Surface and Volume integ

Hermitian skewHermitian and unitary matriceseigenvalues and eigenvectors diagonalisation of matrices CayleyHamilton Theorem Calculus Functions of single variable limit continuity and differentiability Mean value theorems Indeterminate forms and LHos

(what is that?). What . is linear algebra? Functions and equations that arise in the "real world" often involve many tens or hundreds or thousands of variables, and one can only deal with such things by being much more organized than one typically is when treating equations and functions of a single variable. Linear algebra is essentially a ".

Niebles. . and Ranjay Krishna. Stanford Vision and Learning . Lab. 10/2/17. 1. Another, very in-depth linear algebra review from CS229 is available here:. http://cs229.stanford.edu/section/cs229-linalg.pdf.

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