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Jadavpur University: Foundation_Math_forML_Autumn23

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Session 10: Gradient descent, why it works, Linear and Logistic regression, ML estimate

Aug 13, 2023 · Mainak's PMRF Tutorials

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Session 9: Introduction to convex functions, Jensen’s, Holder’s inequality, Minkowski, Lagrangian

Aug 12, 2023 · Mainak's PMRF Tutorials

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Session 8: Inner products, vector norms, dual spaces, introduction to matrix norms

Aug 10, 2023 · Mainak's PMRF Tutorials

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Session 7: Eigenvector decomposition, unitary and normal matrices, Application: PCA and SVD

Aug 9, 2023 · Mainak's PMRF Tutorials

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Session 6: Projections, Least squares, eigenvalue-eigenvectors, Char. polynomial, similar matrices

Aug 6, 2023 · Mainak's PMRF Tutorials

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Session 5: Intro to Matrices, vector spaces, span and basis, 4-fundamental subspaces, elimination

Aug 5, 2023 · Mainak's PMRF Tutorials

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Session 4: MGFs, random vectors, joint distribution, random process, Random walks, Markov chains

Aug 3, 2023 · Mainak's PMRF Tutorials

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Session 3: continuous rvs, pmf, pdf, inequality, Uniform, Exponential, Normal, transformation of rvs

Jul 30, 2023 · Mainak's PMRF Tutorials

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Session 2: Discrete random variables, distribution, expectation, lotus, variance

Jul 29, 2023 · Mainak's PMRF Tutorials

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Session 1: Introduction to counting, RVs, and distributions

Jul 28, 2023 · Mainak's PMRF Tutorials

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