November 2019
Intermediate to advanced
320 pages
13h 35m
French
Content preview from Machine Learning avec Scikit-Learn
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280
Annexe A Solutions des exercices
est utile pour les jeux de données volumineux qui ne tiennent pas
en mémoire, mais elle est plus lente que la PCA ordinaire, c’est
pourquoi vous préférerez cette dernière si le jeu de données tient en
mémoire. La PCA incrémentale est également utile pour les tâches
en ligne, lorsque vous devez effectuer une PCA à la volée, chaque fois
que de nouvelles observations arrivent. La PCA randomisée est utile
lorsque vous voulez réduire considérablement la dimension et que le
jeu de données tient en mémoire: dans ce cas, elle est beaucoup plus
rapide qu’une PCA ordinaire. Enn, la PCA à noyau est utile pour
les jeux ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.