Case studies
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Constrained clustering: bringing balance to the (sales)force
A deep dive into constrained clustering: reformulating K-Means as a linear programming problem to enforce cluster size, revenue or other constraints.
Foundational concepts
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"Impossible" systems of equations and pseudo-inverse
A gentle introduction to pseudo-inverse for solving "impossible" systems of equations with no exact solution. Applications to machine learning included.
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Matrix Reloaded: introduction to matrix calculus
A gentle introduction to matrix calculus for machine learning. Learn derivatives of scalars, vectors and matrices w.r.t. one another. With examples & exercises.
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Thinking inside the Matrix
Master matrix notation for machine learning: convert sums/loops to vector operations and achieve massive performance gains. With examples and exercises.
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