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Topics Covered | Price (USD) | Time |
---|---|---|
Semantic Networks | $80 | 3 hours |
Frames and Scripts | $70 | 2.5 hours |
Logic-Based Knowledge Representation | $90 | 3 hours |
Ontologies and Taxonomies | $85 | 2.5 hours |
Knowledge Representation in AI | $100 | 4 hours |
Application Development | $120 | 5 hours |
Natural Language Processing in AI | $95 | 3.5 hours |
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- Knowledge Representation with Python Dictionaries
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Knowledge Representation with Python Dictionaries
# Example of representing knowledge using a dictionary in Python
knowledge_base = {
"Semantic Networks": ["Concepts", "Relations"],
"Frames": {
"Car": {
"Attributes": ["Color", "Model", "Year"],
"Actions": ["Drive", "Stop", "Park"]
},
"Person": {
"Attributes": ["Name", "Age", "Occupation"],
"Actions": ["Walk", "Talk", "Eat"]
}
},
"Ontologies": {
"Animal": {
"Subclasses": ["Mammal", "Reptile", "Bird"]
},
"Bird": {
"Attributes": ["Feathers", "Beak", "Wings"]
}
}
}
# Accessing information about Frames
car_attributes = knowledge_base["Frames"]["Car"]["Attributes"]
print("Attributes of a Car:", car_attributes)
This code demonstrates a simplified representation of knowledge using a nested dictionary in Python, focusing on Semantic Networks, Frames, and Ontologies concepts within Knowledge Representation.
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