What are the key data structures used in machine learning?
An example of an AI chatbot conversation about data structures in machine learning.
What are the key data structures used in machine learning?
In machine learning, common data structures include arrays, matrices, data frames, and graphs. Each serves different purposes.
Can you explain how arrays are used in machine learning?
Arrays are fundamental for storing data in a structured format, especially for numerical computations and operations.
What about data frames? How do they differ from arrays?
Data frames are more flexible than arrays, allowing for labeled data and different data types in columns, making them ideal for datasets.
Are graphs used in machine learning as well?
Yes, graphs are used in machine learning for representing relationships and structures, especially in social network analysis and recommendation systems.
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