§ About the Levi-Civita symbol
Definition I. Let \(\mathbb{K}\) be a field and consider a matrix \(A\in \text{Mat}_{n\times n}(\mathbb{K})\)
which has index structure \(A^i{}_j\). We define the Levi-Civita symbols \(\epsilon_{i_1i_2\ldots i_n}\)
and \(\epsilon^{i_1i_2\ldots i_n}\) by means of setting:
$$
\det\{A\} := \epsilon_{i_1i_2\ldots i_n}A^{i_1}{}_1A^{i_2}{}_2\cdots A^{i_n}{}_n := \epsilon^{i_1i_2\ldots i_n}A^1{}_{i_1}A^2{}_{i_2}\cdots A^n{}_{i_n}
$$
where \(\det\{\cdot\}\) simply denotes the determinant map.
One can convince themself that this definition suffices to define the totally anti-symmetric symbol. Indeed, for the case
\(n=3\) we may simply write:
$$
\begin{align}
\det\{A\} &= \det \begin{pmatrix} A^1{}_1 & A^1{}_2 & A^1{}_3 \\
A^2{}_1 & A^2{}_2 & A^2{}_3 \\
A^3{}_1 & A^3{}_2 & A^3{}_3
\end{pmatrix} =\\
&= \hphantom{+}A^1{}_1A^2{}_2A^3{}_3 + A^3{}_1A^1{}_2A^2{}_3 + A^2{}_1A^3{}_2A^1{}_3 +\\
&\hphantom{=}- A^3{}_1A^2{}_2A^1{}_3 - A^1{}_1A^3{}_2A^2{}_3 - A^2{}_1A^1{}_2A^3{}_3
\end{align}
$$
which clearly sets \(\epsilon_{123}=\epsilon_{312}=\epsilon_{231}=1\), \(\epsilon_{321}=\epsilon_{132}=\epsilon_{213}=-1\)
being all the components with repeated indices zero.
Let us now take the canonical basis \(\{\mathbf{e}_i\}_{i=1}^n\) of the \(n-\)dimensional \(\mathbb{R}-\)vector space
\(\mathbb{R}^n\), where each vector has \(a-\)th component given by \((\mathbf{e}_i)^a=\delta^a_i\). Similarly, we
introduce the dual canonical basis \(\{\mathbf{e}^i\}_{i=1}^n\) satisfying \((\mathbf{e}^i)_a=\delta^i_a\). There is the natural
identification of \(\{\mathbf{e}_i\}_{i=1}^n\) with column-vectors and of \(\{\mathbf{e}^i\}_{i=1}^n\) with row vectors.
This way of viewing these vectors allows us to define the following matrices:
$$
E = \begin{pmatrix} \mathbf{e}_{\sigma(1)} & \mathbf{e}_{\sigma(2)} & \cdots & \mathbf{e}_{\sigma(n)}\end{pmatrix}
\in \text{Mat}_{n\times n}(\mathbb{K})
$$
where \(\sigma \in S_n\), being \(S_n\) the symmetric group on \(n\) elements. The matrix \(E\) clearly verifies that
its transpose is given by
$$
E^T = \begin{pmatrix} \mathbf{e}^{\sigma(1)} \\ \mathbf{e}^{\sigma(2)} \\ \vdots \\ \mathbf{e}^{\sigma(n)}\end{pmatrix}
\in \text{Mat}_{n\times n}(\mathbb{K})
$$
In index notation, \(E^a{}_b=(\mathbf{e}_b)^a=\delta^a_b\), whereas \((E^T)^a{}_b=(\mathbf{e}^a)_b=\delta^a_b\). This implies
that
$$
\det\{E\}= \epsilon_{i_1i_2\ldots i_n} \delta^{i_1}_{\sigma(1)}\delta^{i_2}_{\sigma(2)}\cdots \delta^{i_n}_{\sigma(n)} =
\epsilon_{\sigma(1)\sigma(2)\ldots \sigma(n)}
$$
and also, using this time the Levi-Civita with the upper indices for computing the determinant of the transpose
$$
\det\{E^T\}= \epsilon^{i_1i_2\ldots i_n} \delta_{i_1}^{\sigma(1)}\delta_{i_2}^{\sigma(2)}\cdots \delta_{i_n}^{\sigma(n)} =
\epsilon^{\sigma(1)\sigma(2)\ldots \sigma(n)}
$$
and since \(\det\{E\}=\det\{E^T\}\) we have:
$$
\epsilon_{\sigma(1)\sigma(2)\ldots \sigma(n)} = \epsilon^{\sigma(1)\sigma(2)\ldots \sigma(n)}
$$
in other words, we do not really care about whether our indices are upstairs or downstairs. Let us now try to compute the
following product:
$$
\begin{align}
\epsilon^{\sigma(1)\sigma(2)\ldots \sigma(n)}\epsilon_{\tau(1)\tau(2)\ldots \tau(n)} &= \det\{E^T\}\det\{E\}=\det\{E^TE\}=\\
&=
\det\left\{\begin{pmatrix} \mathbf{e}^{\sigma(1)} \\ \mathbf{e}^{\sigma(2)} \\ \vdots \\ \mathbf{e}^{\sigma(n)}\end{pmatrix}
\begin{pmatrix} \mathbf{e}_{\tau(1)} & \mathbf{e}_{\tau(2)} & \cdots & \mathbf{e}_{\tau(n)}\end{pmatrix}\right\}=\\
&= \det \begin{pmatrix}
\mathbf{e}^{\sigma(1)}\cdot \mathbf{e}_{\tau(1)} &\mathbf{e}^{\sigma(1)}\cdot \mathbf{e}_{\tau(2)} & \cdots & \mathbf{e}^{\sigma(1)}\cdot \mathbf{e}_{\tau(n)} \\
\mathbf{e}^{\sigma(2)}\cdot \mathbf{e}_{\tau(1)} &\mathbf{e}^{\sigma(2)}\cdot \mathbf{e}_{\tau(2)} & \cdots &\mathbf{e}^{\sigma(2)}\cdot \mathbf{e}_{\tau(n)} \\
\vdots & \vdots & \ddots & \vdots\\
\mathbf{e}^{\sigma(n)}\cdot \mathbf{e}_{\tau(1)} &\mathbf{e}^{\sigma(n)}\cdot \mathbf{e}_{\tau(2)} & \cdots & \mathbf{e}^{\sigma(n)}\cdot \mathbf{e}_{\tau(n)} \\
\end{pmatrix}=\\
&= \det\begin{pmatrix}
\delta^{\sigma(1)}_{\tau(1)} & \delta^{\sigma(1)}_{\tau(2)} & \cdots & \delta^{\sigma(1)}_{\tau(n)}\\
\delta^{\sigma(2)}_{\tau(1)} & \delta^{\sigma(2)}_{\tau(2)} & \cdots & \delta^{\sigma(2)}_{\tau(n)}\\
\vdots & \vdots & \ddots & \vdots\\
\delta^{\sigma(n)}_{\tau(1)} & \delta^{\sigma(n)}_{\tau(2)} & \cdots & \delta^{\sigma(n)}_{\tau(n)}\\
\end{pmatrix}
\end{align}
$$
As before, let us consider the three dimensional case and denote \(\sigma(1)=i, \sigma(2)=j, \sigma(3)=k\) and
\(\tau(1)=l, \tau(2)=m, \tau(3)=n\)
$$
\epsilon^{ijk}\epsilon_{lmn}=
\det \begin{pmatrix}
\delta^i_l & \delta^i_m &\delta^i_n \\
\delta^j_l & \delta^j_m &\delta^j_n \\
\delta^k_l & \delta^k_m &\delta^k_n \\
\end{pmatrix}
$$
Should \(l=i\), then for this product to be non zero clearly \(j\neq i\neq k\), and \(m\neq l \neq n\) and thus,
$$
\epsilon^{ijk}\epsilon_{imn}=
\det \begin{pmatrix}
1 & 0 & 0 \\
0 & \delta^j_m &\delta^j_n \\
0 & \delta^k_m &\delta^k_n \\
\end{pmatrix} =
\delta^j_m\delta^k_n-\delta^j_n\delta^k_m
$$