[6주차 - Day4] ML_basics - Linear Algebra, Matrix Calculus
Python에서의 벡터, 행렬 표현방법 [10.5, 5.2, 3.25, 7.0] [10.5, 5.2, 3.25, 7.0] import numpy as np x = np.array([10.5, 5.2, 3.25]) x.shape (3,) i = 2 x[i] 3.25 np.expand_dims(x, axis=1).shape (3, 1) A = np.array([ [10,20,30], [40,50,60] ]) A array([[10, 20, 30], [40, 50, 60]]) A.shape (2, 3) i = 0 j = 2 A[i, j] 30 j = 1 A[:, j] array([20, 50]) i = 1 A[i, :] array([40, 50, 60]) 행렬의 곱셉 (Matrix Multiplication)..
2023. 5. 14.
