<｜begin▁of▁sentence｜>### Instruction:
Imagine you are a Security Analyst tasked with evaluating the resilience and complexity of a simulated Internet AS (Autonomous System) network. Your assignment involves using the NetworkX library to create a model of this network. Specifically, you are to generate an undirected graph that mirrors the structure of the Internet AS network, consisting of 1500 nodes. This model will serve as the basis for your security analysis. 

Upon successful creation of this network model, your first objective is to assess its size and complexity. To do this, you need to determine two key metrics: the total number of nodes and the total number of edges in this generated network. 

Furthermore, as part of your security assessment, understanding the variety of elements within this network is crucial. Therefore, your second objective is to identify and classify the types of the first 5 nodes within this network. This information is vital for your analysis as it will help you to determine potential vulnerabilities and critical points within the network that may require enhanced security measures.

This task involves practical application of network modeling to simulate real-world scenarios, enabling you to apply your skills in network security analysis.
### Response:
import networkx as nx

# Use random_internet_as_graph to generate a graph resembling the Internet AS network
G = nx.random_internet_as_graph(1500, seed=42)

# Print the number of nodes and edges in the graph
print('Number of nodes:', G.number_of_nodes())
print('Number of edges:', G.number_of_edges())

# Inspect the types of some nodes
for i, node in enumerate(G.nodes(data=True), start=1):
    print('Node', i, ':', node)
    if i == 5: # Limit the output to first 5 nodes
        break
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