Build a solid foundation in Linear Algebra for Machine Learning applications. This course introduces vectors, matrices, and essential operations used in data representation and algorithms, explained with practical Python examples using NumPy. Learn the mathematical principles needed to understand how many machine learning models work.
Prerequisites Basic Python helpful
Level:
Mathematical Notation
Understand and interpret common mathematical symbols and notation used in linear algebra.
Vector Operations
Perform fundamental vector operations such as addition, subtraction, and scalar multiplication.
Matrix Operations
Perform fundamental matrix operations including addition, subtraction, scalar multiplication, and matrix multiplication.
NumPy Implementation
Implement vector and matrix operations using the Python library NumPy.
Data Representation
Recognize how vectors and matrices are used to represent data in machine learning contexts.
Linear Systems
Understand the concept of systems of linear equations and their representation using matrices.