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  1. **Determinant:** A scalar value telling us how much a matrix scales/flips space.
    Ex: For `[[a,b],[c,d]]`, `det = ad - bc`.
    Pro-Tip: `det = 0` means the matrix isn't invertible! Its columns are linearly dependent – no unique solutions!
    #LinearAlgebra #MatrixHacks #STEM #StudyNotes

  2. **Determinant:** A scalar value telling us how much a matrix scales/flips space.
    Ex: For `[[a,b],[c,d]]`, `det = ad - bc`.
    Pro-Tip: `det = 0` means the matrix isn't invertible! Its columns are linearly dependent – no unique solutions!
    #LinearAlgebra #MatrixHacks #STEM #StudyNotes

  3. **Determinant:** A scalar value telling us how much a matrix scales/flips space.
    Ex: For `[[a,b],[c,d]]`, `det = ad - bc`.
    Pro-Tip: `det = 0` means the matrix isn't invertible! Its columns are linearly dependent – no unique solutions!
    #LinearAlgebra #MatrixHacks #STEM #StudyNotes

  4. **Determinant:** A scalar value telling us how much a matrix scales/flips space.
    Ex: For `[[a,b],[c,d]]`, `det = ad - bc`.
    Pro-Tip: `det = 0` means the matrix isn't invertible! Its columns are linearly dependent – no unique solutions!
    #LinearAlgebra #MatrixHacks #STEM #StudyNotes

  5. **Determinant:** A scalar value telling us how much a matrix scales/flips space.
    Ex: For `[[a,b],[c,d]]`, `det = ad - bc`.
    Pro-Tip: `det = 0` means the matrix isn't invertible! Its columns are linearly dependent – no unique solutions!
    #LinearAlgebra #MatrixHacks #STEM #StudyNotes

  6. Alright, future engineers!
    **Matrix Multiplication:** Combining two matrices by taking dot products of rows from the first with columns from the second.
    Ex: `(A_mxn) * (B_nxp) = (C_mxp)`
    Pro-Tip: Inner dimensions (n) MUST match! And remember, `AB ≠ BA` usually!
    #LinearAlgebra #MatrixHacks #STEM #StudyNotes

  7. Alright, future engineers!
    **Matrix Multiplication:** Combining two matrices by taking dot products of rows from the first with columns from the second.
    Ex: `(A_mxn) * (B_nxp) = (C_mxp)`
    Pro-Tip: Inner dimensions (n) MUST match! And remember, `AB ≠ BA` usually!
    #LinearAlgebra #MatrixHacks #STEM #StudyNotes

  8. Alright, future engineers!
    **Matrix Multiplication:** Combining two matrices by taking dot products of rows from the first with columns from the second.
    Ex: `(A_mxn) * (B_nxp) = (C_mxp)`
    Pro-Tip: Inner dimensions (n) MUST match! And remember, `AB ≠ BA` usually!
    #LinearAlgebra #MatrixHacks #STEM #StudyNotes

  9. Alright, future engineers!
    **Matrix Multiplication:** Combining two matrices by taking dot products of rows from the first with columns from the second.
    Ex: `(A_mxn) * (B_nxp) = (C_mxp)`
    Pro-Tip: Inner dimensions (n) MUST match! And remember, `AB ≠ BA` usually!
    #LinearAlgebra #MatrixHacks #STEM #StudyNotes

  10. Alright, future engineers!
    **Matrix Multiplication:** Combining two matrices by taking dot products of rows from the first with columns from the second.
    Ex: `(A_mxn) * (B_nxp) = (C_mxp)`
    Pro-Tip: Inner dimensions (n) MUST match! And remember, `AB ≠ BA` usually!
    #LinearAlgebra #MatrixHacks #STEM #StudyNotes

  11. Alright, future engineers!
    **Matrix Transpose:** Swapping a matrix's rows for its columns.
    Ex: `[[1,2],[3,4]]^T` becomes `[[1,3],[2,4]]`.
    Pro-Tip: `(AB)^T = B^T A^T`. Order matters when transposing products!
    #LinearAlgebra #MatrixHacks #STEM #StudyNotes

  12. Alright, future engineers!
    **Matrix Transpose:** Swapping a matrix's rows for its columns.
    Ex: `[[1,2],[3,4]]^T` becomes `[[1,3],[2,4]]`.
    Pro-Tip: `(AB)^T = B^T A^T`. Order matters when transposing products!
    #LinearAlgebra #MatrixHacks #STEM #StudyNotes

  13. Alright, future engineers!
    **Matrix Transpose:** Swapping a matrix's rows for its columns.
    Ex: `[[1,2],[3,4]]^T` becomes `[[1,3],[2,4]]`.
    Pro-Tip: `(AB)^T = B^T A^T`. Order matters when transposing products!
    #LinearAlgebra #MatrixHacks #STEM #StudyNotes

  14. Alright, future engineers!
    **Matrix Transpose:** Swapping a matrix's rows for its columns.
    Ex: `[[1,2],[3,4]]^T` becomes `[[1,3],[2,4]]`.
    Pro-Tip: `(AB)^T = B^T A^T`. Order matters when transposing products!
    #LinearAlgebra #MatrixHacks #STEM #StudyNotes

  15. Alright, future engineers!
    **Matrix Transpose:** Swapping a matrix's rows for its columns.
    Ex: `[[1,2],[3,4]]^T` becomes `[[1,3],[2,4]]`.
    Pro-Tip: `(AB)^T = B^T A^T`. Order matters when transposing products!
    #LinearAlgebra #MatrixHacks #STEM #StudyNotes