⚑ Smart-World Surf
πŸ”¬ Deep-dive

K-Means

at ΧΧ•Χ Χ™Χ‘Χ¨Χ‘Χ™Χ˜Χͺ Χ‘ΧŸ-Χ’Χ•Χ¨Χ™Χ•ΧŸ Χ‘Χ Χ’Χ‘ Β· Israel
🧭 This concept across all courses β†’

Χ©Χ“Χ¨Χ’Χ• אΧͺ Χ”Χ“Χ£ גם Χ§Χ•Χ‘Χ₯

Χ’Χ¨Χ¨Χ• ΧžΧ‘Χ—ΧŸ, ביכום או Χ¦Χ™ΧœΧ•Χ של ΧžΧ—Χ‘Χ¨Χͺ β€” אני אקרא, אוודא Χ©Χ–Χ” Χ¨ΧœΧ•Χ•Χ Χ˜Χ™, ואחדד אΧͺ Χ”ΧͺΧ•Χ›ΧŸ (ΧžΧ•Χ©Χ’Χ™Χ, Χ‘Χ™Χ›Χ•Χ™Χ™ ΧžΧ‘Χ—ΧŸ, ΧžΧ•ΧžΧ—Χ™Χ•Χͺ).

אם לא Χ‘Χ™ΧžΧ Χͺם β€” Χ”Χ§Χ•Χ‘Χ₯ נקרא ΧœΧ—Χ™ΧœΧ•Χ₯ Χ’Χ•Χ‘Χ“Χ•Χͺ Χ‘ΧœΧ‘Χ“ ואז Χ ΧžΧ—Χ§ ΧžΧ”ΧžΧ’Χ¨Χ›Χͺ (Χ–Χ›Χ•Χ™Χ•Χͺ יוצרים). Χ”Χ’Χ•Χ‘Χ“Χ•Χͺ Χ©Χ ΧœΧžΧ“Χ• נשארוΧͺ Χ•ΧžΧ©Χ€Χ¨Χ•Χͺ אΧͺ Χ”Χ§Χ•Χ¨Χ‘.

K-Means: ΧΧœΧ’Χ•Χ¨Χ™Χͺם ΧΧ©Χ›Χ•ΧœΧ•Χͺ Χ‘ΧœΧͺΧ™ ΧžΧ•Χ Χ—Χ” שמטרΧͺΧ• ΧœΧ—ΧœΧ§ n Χ Χ§Χ•Χ“Χ•Χͺ Χ Χͺונים ל-k ΧΧ©Χ›Χ•ΧœΧ•Χͺ, כאשר Χ›Χœ Χ Χ§Χ•Χ“Χ” Χ©Χ™Χ™Χ›Χͺ ΧœΧΧ©Χ›Χ•Χœ גם Χ”ΧžΧ¨Χ›Χ– Χ”Χ§Χ¨Χ•Χ‘ Χ‘Χ™Χ•ΧͺΧ¨.

The full deep-dive

Two lenses β€” how this course examines the concept, alongside the universal subject expertise. Plus flashcards, worked examples and practice.

πŸ”— Related concepts

More terms from this course

ΧœΧžΧ™Χ“Χ” ΧžΧ•Χ Χ—Χ™Χͺ (Supervised Learning) ΧœΧžΧ™Χ“Χ” Χ‘ΧœΧͺΧ™ ΧžΧ•Χ Χ—Χ™Χͺ (Unsupervised Learning) Χ¨Χ’Χ¨Χ‘Χ™Χ” (Regression) Χ‘Χ™Χ•Χ•Χ’ (Classification) Χ”ΧͺאמΧͺ Χ™ΧͺΧ¨ (Overfitting) ΧͺΧͺ-Χ”ΧͺΧΧžΧ” (Underfitting) Χ”Χ˜Χ™Χ” (Bias) Χ©Χ•Χ Χ•Χͺ (Variance) Χ™Χ¨Χ™Χ“Χͺ Χ’Χ¨Χ“Χ™ΧΧ Χ˜ (Gradient Descent) Χ€Χ•Χ Χ§Χ¦Χ™Χ™Χͺ Χ’ΧœΧ•Χͺ/Χ”Χ€Χ‘Χ“ (Loss Function) ΧΧ™ΧžΧ•Χͺ Χ¦Χ•ΧœΧ‘ (Cross-Validation) Χ”Χ Χ“Χ‘Χͺ ΧžΧΧ€Χ™Χ™Χ Χ™Χ (Feature Engineering) Χ¨Χ’Χ•ΧœΧ¨Χ™Χ–Χ¦Χ™Χ” (Regularization) ΧžΧ˜Χ¨Χ™Χ¦Χͺ Χ‘ΧœΧ‘Χ•Χœ (Confusion Matrix) Χ€Χ•Χ Χ§Χ¦Χ™Χ™Χͺ Χ’Χ¨Χ’Χ™ΧŸ (Kernel Function) Χ¨Χ©Χͺ נוירונים (Neural Network) Χ’Χ₯ Χ”Χ—ΧœΧ˜Χ” (Decision Tree)