Degree Matrix of Fully connected graph https://www.kaggle.com/vipulgandhi/spectral-clustering-detailed-explanation
In this blog post about spectral clustering it states that we can just use the Gaussian Kernel directly.
"Generally we use the Gaussian Kernel K directly, or we form the Graph Laplacian A"
I am confused about how to calculate the degree matrix from a fully connected weighted graph.  And I want to implement this in python.

The degree of a vertex in a fully connected graph is sometimes defined as the sum of the weights of all edges coming from that vertex.
So in other words, the degree $d_i$ of vertex $v_i$ is:
$$
d_i = \sum_j w_{ij}
$$
where $w_{ij}$ is the weight of the edge between vertices $v_i$ and $v_j$.
I have found this pdf to be somewhat helpful in understanding both the algorithm and the mathematical intuition behind why it works:
https://people.csail.mit.edu/dsontag/courses/ml14/notes/Luxburg07_tutorial_spectral_clustering.pdf
