Mathematics for Machine Learning: Matrix Multiplication and (Pseudo) Inverse With NumPy
In this video, we discuss linear algebra routines and matrix multiplications for 2D NumPy arrays, essential for understanding a wide range of machine learning and data science. We use several examples in Python to understand how matrix multiplication works. When analyzing large matrices (i.e., big data sets), we show how to achieve substantial speedups using numpy.linalg.multi_dot. This video also explains matrix transpose, matrix inverse, and pseudo inverse. Finally, we discuss connections between finding pseudo inverse and solving the linear regression problem.
Link to the previous video on NumPy arrays: • Mathematics for Machine Learning: Array, N...
Link to the linear regression video: • Simple Steps to Understand Linear Regressi...
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