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5AM 55

55 exercises to build the ML foundation that will set you apart.


Machine Learning (12 problems)

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Linear Algebra (9 problems)

  • Matrix times Matrix
  • Matrix-Vector Dot Product
  • Transpose of a Matrix
  • Calculate Eigenvalues of a Matrix
  • Singular Value Decomposition (SVD) of 2x2 Matrix
  • Calculate Correlation Matrix
  • Calculate Cosine Similarity Between Vectors
  • Implement Orthogonal Projection of a Vector onto a Line
  • Dot Product Calculator

Probability (9 problems)

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Deep Learning (8 problems)

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Optimization (7 problems)

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Calculus (4 problems)

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Probabilistic ML (3 problems)

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Information Theory (2 problems)

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Linear Algebra for ML (1 problem)

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