Linear Algebra for Machine Learning | Matrix Representation in Linear Regression and Neural Network
Linear Algebra plays a fundamental role in machine learning, in terms of matrix representation and more. In this video we start with introducing basic concepts such as:
1. definition of scalar, vector, matrix, tensor
2. addition, subtraction, multiplication, division, dot product
3. reshape, transpose, inverse
Additionally, we discussed how these concepts have been applied in data science and machine learning, including linear regression and neural network algorithms.
🎬 Videos mentioned in the video:*
• Top 4 Linear Regression Algorithms in...
🗒️ Articles mentioned in the video:
How is Linear Algebra Applied for Machine Learning: / how-is-linear-algebra-applied-for-machine-...
Top 4 Linear Regression Variations in Machine Learning: / top-machine-learning-algorithms-for-regres...
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