home.social

#matrices — Public Fediverse posts

Live and recent posts from across the Fediverse tagged #matrices, aggregated by home.social.

  1. Alright, future engineers!

    The **Determinant** of a square matrix is a scalar value that tells you if the matrix is invertible.
    Ex: For `[[a,b],[c,d]]`, `det = ad - bc`.
    Pro-Tip: If `det = 0`, the matrix is singular (no inverse), meaning `Ax=b` has no unique solution!

    #LinearAlgebra #Matrices #STEM #StudyNotes

  2. Alright, future engineers!
    **Matrix multiplication** combines two matrices, forming a new one where elements are dot products of rows & columns.
    Ex: `(AB)_ij = sum(A_ik * B_kj)`. Inner dimensions must match!
    Pro-Tip: It's NOT commutative (AB != BA)!
    #Matrices #LinearAlgebra #STEM #StudyNotes

  3. Alright, future engineers!

    **Matrix Multiplication** creates a new matrix where `C_ij` is the dot product of row `i` from the 1st matrix & column `j` from the 2nd.

    Ex: `A(2x3) * B(3x2)` gives `C(2x2)`.
    Pro-Tip: Inner dimensions must match!

    #LinearAlgebra #Matrices #STEM #StudyNotes

  4. 🎩🤓 Behold, the blog that bravely attempts to explain the mystical Q, K, V #matrices as if they're the holy trinity of #AI. Spoiler alert: it's mostly a glorified game of 'which word matters?' because we all need another reason to overcomplicate common sense. 🙄🔍
    arpitbhayani.me/blogs/qkv-matr #QKV #Overcomplication #CommonSense #HackerNews #HackerNews #ngated

  5. For all Transf ∈ ℝn×n, the matrix is invertible if and only if rank(Transf) = n

    The #determinant exists if and only if the transformation matrix is square.
    The determinant in a linear transformation is the (signed) area of the image of the fundamental basis formed by the unit square.

    #algebra #matrices #tutorial #determinants #singularity #math #maths #mathematics #mathStodon #ML #machineLearning #systems

  6. #Algebra thread 🧵

    Which #matrices have an inverse?
    Singular matrices never have an inverse.
    When we look at the determinant, the determinant is non-zero for invertible matrices in the same way that non-zero numbers have an inverse.
    Non-zero determinants mean that the matrices has an inverse, and a zero determinant means that the system (of sentences, of graphs) is singular.

    #tutorial #learning #determinants #singularity #math #maths #mathematics #mathStodon #ML #machineLearning #systems

  7. Data returned by an observation typically is represented as a vector in machine learning.

    A neural network can be seen as a large collection of linear models. We may represent the inputs and outputs of each layer as vectors, matrices, and tensors (which are like higher dimensional matrices).

    #algebra #linearAlgebra #vectors #matrices #determinants #singularity #ML #DataScience #math #maths #mathematics #mathStodon #ML #data #dataDon #dataScience #machineLearning #DeepLearning #neuralNetworks

  8. Linear algebra (continued)

    Which of the below operations, when applied to the rows of a matrix, keeps the #singularity (or non-singularity) of the matrix?:
    (Hint: It works the same as a system of linear equations.)

    #learning #algebra #systems #matrices #determinants #singularity #data #ML #DataScience #math #maths #mathematics #mathStodon #tutorial #poll #exercise #exercice #puzzle #calculus

  9. @math

    A system (of sentences, of equations, of graphs) is said "complete" if it has one and only one solution.
    A system is deemed "singular" if it does not have one and only one solution.

    A convenient way to show singularity is to:
    * define a "determinant" as the product of the leading diagonal minus the product of the antidiagonal and
    * calculate that it is zero.

    #learning #algebra #systems #matrices #determinants #singularity #data #ML #DataScience #math #maths #mathematics #tutorial