NetworkX

As explained in Financial AI in Practice

NetworkX is a Python library for creating, manipulating, and studying complex networks.

How Financial AI in Practice covers it

How deep it goes

Builds transaction graphs from tabular data and explores community detection without detailing algorithm internals.

Examples

Uses sample e-commerce transaction data to construct a graph and find potentially suspicious clusters.

What it assumes

Uses foundational graph-data concepts and assumes Python libraries are imported before the exercise.

What you can do after

Apply NetworkX to build and explore transaction graphs and detect potentially suspicious communities.

How it connects

Connects graph analytics with community detection, fraud detection, and graph neural networks.

liveBookmanning.com

Read Financial AI in Practice on liveBook Get the book at manning.com

Also explained in

• 

  liveBookmanning.com
  Graph Neural Networks in ActionNetworkX is a Python library for creating, manipulating, analyzing, and visualizing network and graph structures.

Compare how 2 books explain NetworkX →

Related concepts

• Dijkstra's algorithmimplements · Dijkstra's algorithm computes shortest paths from a source vertex in a weighted graph with nonnegative edge weights.
• graphuses · A graph is a mathematical structure consisting of vertices connected by edges that represent relationships or connections.
• Pythonuses · Python is a high-level, general-purpose, dynamically typed programming language known for readable syntax and automatic memory management.
• GraphRAGused by · GraphRAG is a retrieval-augmented generation approach that uses graph-structured knowledge and relationships to retrieve context for language-model responses.
• data explorationuses · Data exploration is the systematic examination and summarization of data to understand its structure, quality, distributions, relationships, patterns, and anomalies.

This explainer was generated by Manning's knowledge graph from the text of Financial AI in Practice. The section links point to the parts of the book it draws on.