Complete NumPy Linear Algebra Tutorial | From Basics to SVD in Python

Master essential linear algebra operations using Python's NumPy library in this comprehensive tutorial! Perfect for data scientists, ML engineers, and students.

🔍 What you'll learn:
• Creating and manipulating matrices in NumPy
• Essential matrix operations and transformations
• Computing determinants, inverses, and eigenvalues
• Solving systems of linear equations
• Understanding and implementing SVD
• Real-world applications and examples

Chapters :

00:00 - Introduction
00:50 - Matrix Creation and Basic Operations
03:40 - Matrix Properties and Transformations
04:45 - Determinant and Inverse of Matrix
06:00 - Eigen Values and Eigen Vectors
07:00 - Solve Linear Equations using Numpy
08:10 - Singular Value Decomposition using Numpy

💻 Prerequisites:
• Basic Python knowledge
• NumPy installed (pip install numpy)
• Basic understanding of linear algebra concepts

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