Supervised vs. Unsupervised Learning: Which Approach is Right for You?<\/p>\n

Que vous soyez un d\u00e9butant ou un professionnel exp\u00e9riment\u00e9 dans le domaine de l’apprentissage automatique, vous avez probablement entendu parler des deux principaux types d’apprentissage: supervis\u00e9 et non supervis\u00e9. Ces deux approches ont des applications diff\u00e9rentes et peuvent \u00eatre utilis\u00e9es pour r\u00e9soudre diff\u00e9rents probl\u00e8mes.<\/p>\n

L’apprentissage supervis\u00e9 consiste \u00e0 entra\u00eener un mod\u00e8le \u00e0 partir de donn\u00e9es \u00e9tiquet\u00e9es, c’est-\u00e0-dire des donn\u00e9es pour lesquelles la r\u00e9ponse correcte est connue. Ce type d’apprentissage est couramment utilis\u00e9 dans des applications telles que la classification, la r\u00e9gression et la pr\u00e9diction.<\/p>\n

\u00c0 l’inverse, l’apprentissage non supervis\u00e9 consiste \u00e0 entra\u00eener un mod\u00e8le \u00e0 partir de donn\u00e9es non \u00e9tiquet\u00e9es, c’est-\u00e0-dire des donn\u00e9es pour lesquelles la r\u00e9ponse correcte n’est pas connue. Ce type d’apprentissage est couramment utilis\u00e9 dans des applications telles que le regroupement, la r\u00e9duction de dimensionnalit\u00e9 et la d\u00e9tection d’anomalies.<\/p>\n

Chaque approche pr\u00e9sente des avantages et des inconv\u00e9nients. L’apprentissage supervis\u00e9 peut produire des mod\u00e8les pr\u00e9cis et faciles \u00e0 interpr\u00e9ter, mais n\u00e9cessite des donn\u00e9es \u00e9tiquet\u00e9es qui peuvent \u00eatre co\u00fbteuses \u00e0 obtenir. L’apprentissage non supervis\u00e9 peut d\u00e9couvrir des mod\u00e8les cach\u00e9s dans les donn\u00e9es, mais peut \u00eatre plus difficile \u00e0 \u00e9valuer et \u00e0 interpr\u00e9ter.<\/p>\n

En conclusion, le choix entre l’apprentissage supervis\u00e9 et non supervis\u00e9 d\u00e9pendra de la nature des donn\u00e9es et du probl\u00e8me \u00e0 r\u00e9soudre. Il est essentiel de comprendre les avantages et les inconv\u00e9nients de chaque approche afin de choisir celle qui convient le mieux \u00e0 votre cas d’utilisation sp\u00e9cifique.<\/p>\n","protected":false},"excerpt":{"rendered":"

Supervised vs. Unsupervised Learning: Which Approach is Right for You? Que vous soyez un d\u00e9butant ou un professionnel exp\u00e9riment\u00e9 dans 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