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Learn linear algebra in this course for beginners. This course covers the linear algebra skills needed for data science, machine learning, and AI, with a focus on practical applications and real-world examples.
✏️ Course developed by @LunarTech_ai
Learn more linear algebra with this 25+ hour course: https://academy.lunartech.ai/product/fundamentals-to-linear-algebra
⭐️ Contents ⭐️
⌨️ (0:00:00) Introduction to the course
⌨️ (0:08:30) Linear Algebra Roadmap for 2024
⌨️ (0:27:50) Course Prerequisites
⌨️ (0:36:05) Refreshment: Real Numbers and Vector Spaces
⌨️ (0:40:18) Refreshment: Norms and Euclidean Distance
⌨️ (0:52:13) Why These Prerequisites Matter
⌨️ (0:54:40) Foundations of Vectors
⌨️ (1:03:22) Vector – Geometric Representation Example
⌨️ (1:25:35) Special Vectors
⌨️ (1:38:13) Application of Vectors
⌨️ (1:50:25) Vectors Operations and Properties
⌨️ (2:24:14) Advanced Vectors and Concepts
⌨️ (2:49:14) Length of a Vector – def and example
⌨️ (2:54:33) Length of Vector – Geometric Intuition
⌨️ (3:05:31) Dot Product
⌨️ (3:20:00) Dot Product, Length of Vector and Cosine Rule
⌨️ (3:34:00) Cauchy Schwarz Inequality – Derivation & Proof
⌨️ (3:48:11) Introduction to Linear Systems
⌨️ (4:03:53) Introduction to Matrices
⌨️ (4:20:02) Core Matrix Operations
⌨️ (5:00:41) Solving Linear Systems – Gaussian Elimination
⌨️ (5:29:59) Detailed Example – Solving Linear Systems
⌨️ (5:45:46) Detailed Example – Reduced Row Echelon Form (Augmented Matrix,REF, RREF)
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