Machine Learning
Machine Learning · 11. mai 2024
Advanced algorithms enable computers to identify patterns, make decisions, and even predict the future based on data. Among these powerful tools, the Support Vector Machine (SVM) is notable for its effectiveness, especially in the field of classification.
But how does it work?
Let's demystify this algorithm, starting with one of its fundamental concepts: the hyperplane.
Imagine you're at a park and you observe a wide, open field with various types of flowers scattered all around.
Machine Learning · 11. mai 2024
L’algorithme de la machine à vecteurs de support (SVM) sépare efficacement les données en trouvant l’hyperplan optimal qui maximise la marge entre les catégories. Cette approche robuste améliore la classification et la prédiction de nouvelles données.
Machine Learning · 29. avril 2023
K-Means clustering: think of it as organizing a room full of strangers into smaller friend groups based on shared interests. Similarly, K-Means groups data points based on their similarities. In finance, this helps in classifying customers, investments, or market trends. By uncovering hidden patterns, K-Means offers valuable insights, guiding better decisions in portfolio management and customer service. A handy tool for making sense of vast data!
Machine Learning · 29. avril 2023
K-Means clustering: think of it as organizing a room full of strangers into smaller friend groups based on shared interests. Similarly, K-Means groups data points based on their similarities. In finance, this helps in classifying customers, investments, or market trends. By uncovering hidden patterns, K-Means offers valuable insights, guiding better decisions in portfolio management and customer service. A handy tool for making sense of vast data!