For The Love Of Directed Acyclic Graphs

DAG stands for

Directed Acyclic Graph.

A visual map of models,

Connections in a data path.

Data science offers an

Efficient way to map it out,

Graphing workflows and

Pipelines, no doubt.

Starting from a node,

Following edges on a path,

Connections weaving data stories,

Avoiding cycles’ aftermath.

A node is a vertex in the graph,

An edge connects two nodes with a path.

A cycle or loop winds through,

Starting and ending at nodes, it’s true!

In acyclic graphs,

No loops or cycles abound.

No path allows from

Node A and back around.

In the context of

Directed Acyclic Graphs,

“Directed” refers to directionality

Of edges between nodes.

To wrap things up, a DAG is simply

A graph with both these properties:

All edges must have directions,

But cycles shall never be allowed!

If I can write poetry about graph theory,

I can do ANYTHING!

I recently wrote a poem about Directed Acyclic Graphs (DAGs) to combine my love for writing and teaching data science concepts. Expressing complex concepts in unique ways inspires innovative thinking.