[Shorts 선형대수학]
1.[Shorts 선형대수학] Vectors-1
👨🏫 본 글은 칸 아카데미(https://www.khanacademy.org/math/linear-algebra/vectors-and-spacesVector intro for linear algebraReal corrdinate spacesAdding v
2.[Shorts 선형대수학] Vectors-2
👨🏫 본 글은 칸 아카데미(https://www.khanacademy.org/math/linear-algebra/vectors-and-spacesVector examplesUnit vectors introParametric representations o
3.[Shorts 선형대수학] Linear Combinations and span
👨🏫 본 글은 칸 아카데미(https://www.khanacademy.org/math/linear-algebra/vectors-and-spacesLinear combinations and span🎈 선형 결합이란 위에서 볼 수 있듯이, 상수배를 한 벡터
4.[Shorts 선형대수학] Linear dependence and independence
👨🏫 본 글은 칸 아카데미(https://www.khanacademy.org/math/linear-algebra/vectors-and-spaces- Introduce to linear independencemore on linear independeces
5.[Shorts 선형대수학] Subspaces and the basis for a subspace 1
👨🏫 본 글은 칸 아카데미(https://www.khanacademy.org/math/linear-algebra/vectors-and-spaces- Linear subspace🎈 오늘은 선형 부분공간(linear subspace)에 대해 학습합니다. 우
6.[Shorts 선형대수학] Subspaces and the basis for a subspace 2
👨🏫 본 글은 칸 아카데미(https://www.khanacademy.org/math/linear-algebra/vectors-and-spaces- Basis of a subspace🎈 오늘은 Basis of subspace, 부분공간의 기저에 대해 알
7.[Shorts 선형대수학] Vector dot and cross products 1 (dot product)
👨🏫 본 글은 칸 아카데미(https://www.khanacademy.org/math/linear-algebra/vectors-and-spaces- Vector dot product propertiesProving vector dot product pro
8.[Shorts 선형대수학] Vector dot and cross products 2 (Cauchy-Schwarz inequality)
👨🏫 본 글은 칸 아카데미(https://www.khanacademy.org/math/linear-algebra/vectors-and-spaces- Proof of the Cauchy-Schwarz inequality🎈 오늘은 코시-슈바르츠 부등식에 대
9.[Shorts 선형대수학] Vector dot and cross products 3 (triangle inequality)
👨🏫 본 글은 칸 아카데미(https://www.khanacademy.org/math/linear-algebra/vectors-and-spaces- Vector triangle inequality🎈 오늘은 백터의 삼각부등식에 대해 학습합니다. 이전 수업
10.[Shorts 선형대수학] Vector dot and cross products 4 (Defining the angle)
👨🏫 본 글은 칸 아카데미(https://www.khanacademy.org/math/linear-algebra/vectors-and-spaces- Defining the angle betweens Vectors🎈 오늘은 벡터 간의 각도에 대해 학습합니
11.[Shorts 선형대수학] Vector dot and cross products 5 (Normal vector and Cross product)
👨🏫 본 글은 칸 아카데미(https://www.khanacademy.org/math/linear-algebra/vectors-and-spaces- Defining a plane in $\\mathbb{R}^3$ with a point and normal
12.[Shorts 선형대수학] Vector dot and cross products 6 (vector and plane)
👨🏫 본 글은 칸 아카데미(https://www.khanacademy.org/math/linear-algebra/vectors-and-spaces- Vector triple product expansion(very optional)Normal vector
13.[Shorts 선형대수학] Vector dot and cross products 7 (Dot and Cross product)
👨🏫 본 글은 칸 아카데미(https://www.khanacademy.org/math/linear-algebra/vectors-and-spaces- Dot and Cross product Comparison/inituition🎈 오늘은 외적과 내적에 대
14.[Shorts 선형대수학] Vector dot and cross products 8 (Distance between plane)
👨🏫 본 글은 칸 아카데미(https://www.khanacademy.org/math/linear-algebra/vectors-and-spaces- Distance between plane🎈 오늘 평면사이의 두 거리를 구하는 방법을 학습합니다. 본 쳅터
15.[Shorts 선형대수학] Matrices for solving systems by elimination
👨🏫 본 글은 칸 아카데미(https://www.khanacademy.org/math/linear-algebra/vectors-and-spaces- Solving a system of 3 equations and 4 variables using matri
16.[Shorts 선형대수학] Null space and column space 1
👨🏫 본 글은 칸 아카데미(https://www.khanacademy.org/math/linear-algebra/vectors-and-spaces-
17.[Shorts 선형대수학] Null space and column space 2
👨🏫 본 글은 칸 아카데미(https://www.khanacademy.org/math/linear-algebra/vectors-and-spaces- Visualizing a column space as a plane in $R_3$\
18.[Shorts 선형대수학] Functions and linear transformations
👨🏫 본 글은 칸 아카데미(https://www.khanacademy.org/math/linear-algebra/vectors-and-spaces- A more formal understanding of functionsVector transformati
19.[Shorts 선형대수학] Linear Transformation Examples
👨🏫 본 글은 칸 아카데미(https://www.khanacademy.org/math/linear-algebra/vectors-and-spaces- Linear transformation examples: Scaling and reflectionsLine
20.[Shorts 선형대수학] Transpose of a matrix
👨🏫 본 글은 칸 아카데미(https://www.khanacademy.org/math/linear-algebra/vectors-and-spaces- Transpose of a matrixDeterminant of transpose🎈 이번 강의에서는 Tr
21.[Shorts 선형대수학] Orthogonal complements
👨🏫 본 글은 칸 아카데미(https://www.khanacademy.org/math/linear-algebra/vectors-and-spaces- Orthogonal complementsdim(v) + dim(orthogonal complement of