EEE465 Numerical Methods for Artificial Intelligence
lecture notes from: Matrix Methods in Machine Learning, Laurent Lessard
DERS UYGULAMA BELGESİ (SYLLABUS)
weekly schedule
resources
lecture videos
Matrix Methods in Machine Learning, Laurent Lessard
textbooks (linear algebra)
Introduction to Applied Linear Algebra – Vectors, Matrices, and Least Squares (Boyd&Vandenberghe)
Linear Algebra for Everyone (Strang)
Linear Algebra and Learning from Data (Strang)
textbooks (optimization)
An Introduction to Optimization (Chong&Zak)
Constrained Optimization and Lagrange Multiplier Methods (Bertsekas)
Convex Optimization: Algorithms and Complexity (Bubeck)
Convex Optimization (Boyd&Vandenberghe)
textbooks (machine learning)
Matrix Methods in Data Mining and Pattern Recognition (Eldén)
Learning from Data (Abu-Mostafa&Magdon-Ismail&Lin)
Mathematics for Machine Learning (Deisenroth&Faisal&Ong)
Deep Learning (Goodfellow&Bengio&Courville)
Neural Networks and Deep Learning (Nielsen)
Youtube playlists
Introduction to Applied Linear Algebra (Stephen Boyd)
Linear Algebra (Gilbert Strang)
Essence of Linear Algebra (3Blue1Brown)
Convex Optimization (Visually Explained)
Intro to Data Science (and Machine Learning) (Steve Brunton)
Introduction to Statistics and Data Analysis (Steve Brunton)
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