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List of folders adapted to new notation:
- A1.Optimization
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- R1. Regression Intro
- R2. Regression k-NN
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- R4.Regression_ML
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- R5.Bayesian_Regression
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- R3. Least squares
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- R6.Gaussian_Processes
- R7.Regression_Overview
- R_lab1_Bay_GP_Regresion_v_py2
- R_lab1_ML_Bay_Regresion
- R_lab2_GP
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- Ejercicios 1 - 16 (optimización y regresión)
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- Exercises 17-end.
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- C1 Intro Classification
- C2 kNN classification
- C3 Classification LogReg
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- C4 Classification SVM
- C lab 1 Classification (no tenía notación, únicamente erratas menores)
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- U1 K-means: usual input sample indexing, k=0,..., K-1, is replaced here by
$\ell =0, ..., L-1$ to use K for the number of groups and k for the groups.
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- TM1-NLP. No notation changes.
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- U2 Spectral clustering.
$K$ is used here for the kernel function, the affinity matrix and the number of K-means groups. To avoid overusing$K$ , I have used$N$ for the number of samples. Also, I have not used$k$ for the sample index (so as to avoid K_{kl}). Using i, j and n in this notebook makes a bit more sense, specially because samples i and j are used to compute component Kij of the affinity matrix.
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- U_lab1: a single notation change. U_lab1 contains draft versions only, at this time.
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- TM2, TM3, TM4. No notation changes.
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- E_lab1: old notation unchanged, because it is being used for other courses (TMDE).
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