<｜begin▁of▁sentence｜>### Instruction:
As an industrial designer, you have been tasked with creating a new product for mass production. You have decided to develop a smart home device that uses a network to analyze and understand user behavior within the home. To achieve this, you want to obtain embeddings for a simulated network of smart home devices to facilitate behavior analysis. The network will consist of 100 nodes, representing the devices, and will have a probability of edge creation of 0.5 to simulate the connections between these devices. This will help in creating a more intuitive and user-friendly smart home device.
### Response:
import networkx as nx
from karateclub import Node2Vec

# Create a graph
g = nx.gnp_random_graph(100, 0.5)

# Initialize Node2Vec model
model = Node2Vec(walk_number=10, walk_length=80, p=1, q=1, dimensions=128, workers=4, window_size=5, epochs=1, learning_rate=0.05, min_count=1, seed=42)

# Fit the model
model.fit(g)

# Get the embedding
embedding = model.get_embedding()

print('Embedding shape:', embedding.shape)
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