data matrices
数据矩阵
identity matrices
单位矩阵
sparse matrices
稀疏矩阵
random matrices
随机矩阵
orthogonal matrices
正交矩阵
square matrices
方阵
symmetric matrices
对称矩阵
diagonal matrices
对角矩阵
block matrices
块矩阵
positive matrices
正矩阵
mathematics often involves working with matrices.
数学通常涉及处理矩阵。
we can represent data using multiple matrices.
我们可以使用多个矩阵表示数据。
in computer graphics, matrices are used for transformations.
在计算机图形学中，矩阵用于变换。
solving systems of equations often requires manipulating matrices.
求解方程组通常需要操作矩阵。
we learned how to add and subtract matrices in class.
我们在课堂上学习了如何加减矩阵。
eigenvalues and eigenvectors are important concepts in matrix theory.
特征值和特征向量是矩阵理论中的重要概念。
in machine learning, we often use matrices to represent features.
在机器学习中，我们通常使用矩阵表示特征。
matrix multiplication is not commutative.
矩阵乘法不是交换的。
we can find the inverse of a matrix if it is non-singular.
如果矩阵是非奇异的，我们可以找到它的逆。
applications of matrices include computer graphics and physics simulations.
矩阵的应用包括计算机图形学和物理模拟。
data matrices
数据矩阵
identity matrices
单位矩阵
sparse matrices
稀疏矩阵
random matrices
随机矩阵
orthogonal matrices
正交矩阵
square matrices
方阵
symmetric matrices
对称矩阵
diagonal matrices
对角矩阵
block matrices
块矩阵
positive matrices
正矩阵
mathematics often involves working with matrices.
数学通常涉及处理矩阵。
we can represent data using multiple matrices.
我们可以使用多个矩阵表示数据。
in computer graphics, matrices are used for transformations.
在计算机图形学中，矩阵用于变换。
solving systems of equations often requires manipulating matrices.
求解方程组通常需要操作矩阵。
we learned how to add and subtract matrices in class.
我们在课堂上学习了如何加减矩阵。
eigenvalues and eigenvectors are important concepts in matrix theory.
特征值和特征向量是矩阵理论中的重要概念。
in machine learning, we often use matrices to represent features.
在机器学习中，我们通常使用矩阵表示特征。
matrix multiplication is not commutative.
矩阵乘法不是交换的。
we can find the inverse of a matrix if it is non-singular.
如果矩阵是非奇异的，我们可以找到它的逆。
applications of matrices include computer graphics and physics simulations.
矩阵的应用包括计算机图形学和物理模拟。
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