Code Lab
🏠 Home
⚡ Code Lab
🧠 ML Studio
🔧 ML Tools
📚 LMS ↗
🌙
☰
📐 NumPy
Theme: Dracula
Material Dark
Nord
Default
Auto-run on Ctrl+Enter
🗑 Clear
📋 Copy
🔗 Share
▶ Run
# NumPy — numerical computing import numpy as np # Arrays a = np.array([1, 2, 3, 4, 5], dtype=np.float64) b = np.random.randn(3, 3) print("Array:", a) print("Sum:", a.sum(), "| Mean:", a.mean(), "| Std:", round(a.std(), 4)) # Matrix operations A = np.array([[1,2],[3,4]]) B = np.array([[5,6],[7,8]]) print("\nMatrix A:\n", A) print("A @ B:\n", A @ B) print("Eigenvalues:", np.linalg.eigvals(A).round(4)) # Broadcasting x = np.arange(12).reshape(3, 4) print("\nReshaped (3x4):\n", x) print("Row norms:", np.linalg.norm(x, axis=1).round(3))
OUTPUT
Ready
✕ Clear
▶ Press Run or Ctrl+Enter to execute your code.
✕
🏠 Home
⚡ Code Lab
🧠 ML Studio
🔧 ML Tools
