Makine Öğrenmesi Perde 1: Matematiksel Altyapı

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Zekânın Matematikle İmtihânı ( Resim kaynağı )

Episot 1.1 - Temel Matematik

Çevrimiçi Ders

Data Science Math Skills - Daniel Egger ve Paul Bendich, Duke University, coursera


Episot 1.2 - Lineer Cebir

Matrix Operations, Projections, Eigenvalues & Eigenvectors, Vector Spaces and Norms Principal Component Analysis (PCA), Singular Value Decomposition (SVD), Eigendecomposition of a matrix, LU Decomposition, QR Decomposition/Factorization, Symmetric Matrices, Orthogonalization & Orthonormalization,


Yazı-Makale



Kalid Azad - BetterExplained - Yazı dizisi
Kalid Azad - BetterExplained
Kalid Azad - BetterExplained
David Austin - Grand Valley State University - American Mathematical Society


Kitaplar





Çevrimiçi Dersler

Sal Khan - Khan Academy
Gilbert Strang - MIT
Maggie Myers ve Robert van de Geijn - The University of Texas at Austin - edX
Gilbert Strang - Mathworks 






Ders Notları

Kunal Shah - Stanford University






Episot 1.3 Fonksiyonel Analiz

Kitaplar
Analysis Now
Gert K. Pedersen
A Course in Functional Analysis
John B. Conway



Ders İçeriği




Episot 1.4 Gerçel ve Karmaşık Analiz
Sets and Sequences, Topology, Metric Spaces, Single-Valued and Continuous Functions, Limits, Cauchy Kernel, Fourier Transforms


Episot 1.5 Çok Değişkenli Analiz

Differential and Integral Calculus, Partial Derivatives, Vector-Values Functions, Directional Gradient, Hessian, Jacobian, Laplacian and Lagragian Distribution.


Multivariable Calculus - Khan Academy


Episot 1.6 Makine Öğrenmesi için Matematik



Math for Machine Learning - Hal Daume (ders notları)
Mathematics of Machine Learning - Philippe Rigollet - MIT


Sahne 1.10.1 -  Makine Öğrenmesi için Lineer Cebir



Linear Algebra for machine learning - David Barber - University College London  - Video
Machine Learning - 03. Linear Algebra Review - Andrew Ng - Coursera - Ders Videosu
Linear Algebra - Deep Learning - Kitap bölümü

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