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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

Large Language Model (LLM)

A Large Language Model refers to a type of advanced Artificial Intelligence model designed to exhibit human-like language understanding and generation abilities. LLMs are…

Speech Recognition

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Support Vector Machines

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Deep Reinforcement Learning

Deep Reinforcement Learning is a subset of Machine Learning that combines Deep Learning and Reinforcement Learning. It involves training AI models to make decisions…
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