Proof of linear independence of dummy encoding I understand one-hot encoding is linearly dependent and if I drop one column, it would become linear independent, but I don't know how to prove it, can someone give me a mathematical proof.

Start with the definition:

A sequence of vectors $\mathbf{v}_1, \mathbf{v}_2, \dots,
 \mathbf{v}_k$ from a vector space $V$ is said to be linearly
dependent, if there exist scalars $a_1, a_2, \dots, a_k$, not all
zero, such that
$$a_1\mathbf{v}_1 + a_2\mathbf{v}_2 + \cdots + a_k\mathbf{v}_k =
 \mathbf{0},$$
where $\mathbf{0}$ denotes the zero vector.

One-hot encoded matrix looks like
$$
\begin{bmatrix}
1 & 0 & 0 \\
0 & 1 & 0 \\
0 & 0 & 1 \\
\end{bmatrix} 
$$
now add an intercept to the matrix:
$$
\begin{bmatrix}
1 & 1 & 0 & 0 \\
1 & 0 & 1 & 0 \\
1 & 0 & 0 & 1 \\
\end{bmatrix}  
$$
You should not have problems finding non-zero vectors such that after multiplying the new matrix by them you would get zero vectors (e.g. $(-\pi, \pi, \pi, \pi)$). This shows that the columns are linearly dependent, so multicollinear. That is why we drop one of the columns per each feature.
