# Vector Space of Linear Transformations

Suppose we have linear transformations $T : V \to W$ for finite dimensional vector spaces $V$ and $W$.
We can certainly think of $\mathcal{L}(V,W)$ as a vector space of all those transformations (provided addition and multiplication by scalar of transformations are defined and satisfy certain axioms).

While a vector space doesn't really need a basis and a dimension to exist, is there any meaning for a basis and dimension of this vector space $\mathcal{L}(V,W)$? Suppose $V$ is $n$-dimensional and $W$ is $m$-dimensional, what would be the dimension of $\mathcal{L}(V,W)$?

I was trying to make an analogy for the matrix representation of a linear transformation $T:V \to W$ as simply an isomorphism from $\mathcal{L}(V,W)$ to $F^{n\times m}$, the vector space of all $n \times m$ matrices over the field $F$.

Any clue about those points ?

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A good reference for this is Section 2.4 from Linear Algebra by Friedberg et al. –  BU982T Apr 24 '13 at 20:06

Yes, there is meaning for basis and dimension for $L(V,W)$, and they have meaning for every other vector space for that matter.
The dimension is $\dim(V)*\dim(W)$.
Yes, you can show that $L(V,W)\cong M_{\dim(V),\dim(W)}(\Bbb F)$ in such a way that evaluation of these transformations corresponds to matrix multiplication.