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⌨️ Why These Prerequisites Matter
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Classroom Contents
Linear Algebra for Machine Learning and Generative AI
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- 1 ⌨️ Introduction to the course
- 2 ⌨️ Linear Algebra Roadmap for 2024
- 3 ⌨️ Course Prerequisites
- 4 ⌨️ Refreshment: Real Numbers and Vector Spaces
- 5 ⌨️ Refreshment: Norms and Euclidean Distance
- 6 ⌨️ Why These Prerequisites Matter
- 7 ⌨️ Foundations of Vectors
- 8 ⌨️ Vector - Geometric Representation Example
- 9 ⌨️ Special Vectors
- 10 ⌨️ Application of Vectors
- 11 ⌨️ Vectors Operations and Properties
- 12 ⌨️ Advanced Vectors and Concepts
- 13 ⌨️ Length of a Vector - def and example
- 14 ⌨️ Length of Vector - Geometric Intuition
- 15 ⌨️ Dot Product
- 16 ⌨️ Dot Product, Length of Vector and Cosine Rule
- 17 ⌨️ Cauchy Schwarz Inequality - Derivation & Proof
- 18 ⌨️ Introduction to Linear Systems
- 19 ⌨️ Introduction to Matrices
- 20 ⌨️ Core Matrix Operations
- 21 ⌨️ Solving Linear Systems - Gaussian Elimination
- 22 ⌨️ Detailed Example - Solving Linear Systems
- 23 ⌨️ Detailed Example - Reduced Row Echelon Form Augmented Matrix,REF, RREF
