# The DeepWalk Algorithm

Learn the DeepWalk algorithm for node embedding.

## We'll cover the following

## What is the DeepWalk algorithm?

The **DeepWalk algorithm** is an embedding generator algorithm, which means it receives a graph as an input and then outputs the embedding of the nodes of this graph as a vector representation.

This algorithm was proposed in 2014 as a way of learning representations for social online relationships and uses random walks as a core concept.

### Random walk and similarity

The algorithm makes the assumption that nodes that are adjacent should have similar embeddings because they are similar in the network. Therefore, the concept of homophily** **is essential. **Homophily** states that similar nodes tend to connect in a network. In other words, if two nodes are expected to share some characteristic, such as having the same job, we say that this network has a homophily characteristic.

In order to assess the similarity between those nodes, we set, for each node,

For example, let’s consider the graph below with

Get hands-on with 1200+ tech skills courses.