What are embedding techniques in AI?
An example of an AI chatbot conversation about embedding techniques in AI.
What are embedding techniques in AI?
Embedding techniques are methods used to convert categorical data into numerical vectors, making it easier for AI models to process.
Can you give me some examples of embedding techniques?
Sure! Common examples include Word2Vec, GloVe, and more recently, BERT for text data.
How do these techniques improve machine learning models?
They help capture semantic relationships and contextual meanings, leading to better performance in tasks like classification and clustering.
Are there any limitations to using embedding techniques?
Yes, they can sometimes lead to loss of information and may not capture rare or out-of-vocabulary words effectively.
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