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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…

Ensemble Learning

Ensemble Learning involves combining multiple Machine Learning models to achieve superior performance and accuracy. By leveraging the “wisdom of the crowd,” Ensemble Learning mitigates…

Fuzzy Logic

Fuzzy Logic is a mathematical framework that deals with uncertainty and imprecision. By assigning degrees of truth to statements, Fuzzy Logic allows businesses to…

Convolutional Neural Network

A convolutional neural network is a powerful deep learning model designed for processing and analysing visual data. It excels in tasks such as image…
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