Comments (1)
Concernant l'erreur des exemples dans l'exercice 2 (et non pas exercice 3):
Il y avait effectivement une erreur (presence du facteur 0.5) dans la formule de la descente de gradient de la methode fit, les valeurs de theta1, predict(theta1,X1), theta2 et predict(theta2,X2) post fit sont desormais corrigées.
Concernant l'erreur de le 04 et 05:
Une précision a été apporté comme quoi il faut appeler predict au sein de mse (dans l'exercice 4), celle-ci spécifie aussi que les 2 arguments seront bien X et Ytrue comme arguments dans les methodes des metrics des exercices qui suivent et qu'il faut donc appeler predict au sein de la methode de la metric.
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Related Issues (20)
- ML00 ex00: return type of Matrix * Vector
- ML00 ex06: wrong return description
- ML00 ex08: Interlude + Examples' cost
- ML00 ex01 (correction): Wrong examples HOT 4
- ML01 ex03: Wrong loss_elem_ examples
- ML03 ex03 epsilon should be added to y_hat, not y
- ML01 ex05 (z_score): incoherent example
- ML03 ex06 difference of arguments between definition and examples
- ML02 ex05 (mylinearregression): multiple issues (examples, syntax)
- ML02 ex03 (gradient): name syntax
- ml04ex07 wrong number of curves asked
- Day04 ex08 : Typo "penalty" in the subject, "penality" in the examples
- Day04 ex09 : incoherences in the subject
- Fix the Pipeline to automatically push the subjects to the repo
- Name mismatch between definition and example
- 1 instead of 1.0
- missing a parameter in the thetas
- Uppercase instead of lowercase
- X, Y instead of y, y_hat
- missing epsilon
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