<｜begin▁of▁sentence｜>### Instruction:
As a Web Content Manager responsible for maintaining an educational platform, you've been tasked with enhancing the platform's features to include node embeddings for network analysis. Your team has collected data on student interactions within the platform, resulting in a network graph with 100 nodes representing students. Each connection between nodes signifies an interaction between two students. With a connection probability of 0.05, you need to utilize the RandNE model to generate node embeddings based on these interactions. This will enhance the platform's analytical capabilities, allowing for better understanding of student engagement and collaboration patterns.
### Response:
import networkx as nx
from karateclub import RandNE

# Create a graph
G = nx.fast_gnp_random_graph(100, 0.05, seed=42)

# Initialize RandNE model with default parameters
model = RandNE()

# Fit the model on the graph
model.fit(G)

# Retrieve the embeddings
embeddings = model.get_embedding()

print(embeddings)
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