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What is Word Embeddings?

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Word Embeddings are a technique in NLP that represent words as continuous vectors in a high-dimensional space. These vectors capture semantic and syntactic relationships between words. Word embeddings are useful for tasks such as language translation, sentiment analysis, and document clustering.

Other Definitions

Multi-Agent Systems

Multi-Agent Systems are AI systems where multiple autonomous agents interact and collaborate to accomplish a goal. These agents can be software programs, robots, or…

Decision Networks

Decision networks, also known as Probabilistic Graphical Models, are a type of AI model that represents uncertain knowledge using a graph structure. Decision Networks…

Graph Neural Networks

Graph Neural Networks are machine learning models designed to handle data structured as graphs. They can capture relationships and dependencies between entities and perform…

Reinforcement Learning

Reinforcement Learning is a branch of AI that focuses on training agents to make decisions through trial and error in a specific environment. By…
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