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Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - Mathematical Foundation: SubSpace
In this video, we will cover SubSpace.
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This clip is from the chapter "Machine Learning: Feature Engineering and Dimensionality Reduction with Python" of the series "Data Science and Machine Learning (Theory and Projects) A to...
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This clip is from the chapter "Machine Learning: Feature Engineering and Dimensionality Reduction with Python" of the series "Data Science and Machine Learning (Theory and Projects) A to...
Curated Video
Practical Data Science using Python - Principal Component Analysis - Computations 2
This video explains Eigenvalues and Eigenvectors.<br<br/>/>
This clip is from the chapter "Dimensionality Reduction Using PCA" of the series "Practical Data Science Using Python".This section explains dimensionality reduction using PCA.
This clip is from the chapter "Dimensionality Reduction Using PCA" of the series "Practical Data Science Using Python".This section explains dimensionality reduction using PCA.
Khan Academy
Khan Academy: Linear Algebra: Rank(a) = Rank (Transpose of A)
A video lesson showing why the rank of a matrix is the equal to the rank of that matrix's transpose. [11:13]
Khan Academy
Khan Academy: Linear Algebra: Coordinates With Respect to a Basis
A video lesson showing that vectors in space can be defined by coordinates with respect to a basis. A concrete example is given for a vector in R2. Shows how the vector is defined in traditional Cartesian coordinates and then how it can...
Khan Academy
Khan Academy: Linear Algebra: Rank(a) = Rank (Transpose of A)
A video lesson showing why the rank of a matrix is the equal to the rank of that matrix's transpose. [11:13]