Podcast
Questions and Answers
What is a major issue with one-hot encoding of words?
What is a major issue with one-hot encoding of words?
- Inability to handle out-of-vocabulary words
- High training efficiency
- High dimensionality of vectors (correct)
- Capture of synonymous words
What is the main advantage of using Word2Vec over traditional one-hot encoding?
What is the main advantage of using Word2Vec over traditional one-hot encoding?
- Ability to handle out-of-vocabulary words
- Ability to capture synonymous words (correct)
- Ability to work with rare words
- Higher training efficiency
What is the main difference between CBOW and Skip-Gram models?
What is the main difference between CBOW and Skip-Gram models?
- CBOW is faster to train, while Skip-Gram is more accurate (correct)
- CBOW is more accurate, while Skip-Gram is faster to train
- CBOW is better for capturing synonyms, while Skip-Gram is better for capturing antonyms
- CBOW works better with rare words, while Skip-Gram works better with frequent words
What is the main limitation of Word2Vec models?
What is the main limitation of Word2Vec models?
What is the main application of Concept Embedding?
What is the main application of Concept Embedding?
What is the current state of the art for NLP tasks?
What is the current state of the art for NLP tasks?
What is the primary motivation for building a better vector representation of words?
What is the primary motivation for building a better vector representation of words?
What is a benefit of using CBOW over Skip-Gram models?
What is a benefit of using CBOW over Skip-Gram models?
What is the purpose of distributional hypothesis in word embeddings?
What is the purpose of distributional hypothesis in word embeddings?
What is a limitation of traditional one-hot encoding of words?
What is a limitation of traditional one-hot encoding of words?
What is the goal of Concept Embedding?
What is the goal of Concept Embedding?
What is a benefit of using transformer models for NLP tasks?
What is a benefit of using transformer models for NLP tasks?
What is the purpose of projecting unannotated images into the multidimensional space?
What is the purpose of projecting unannotated images into the multidimensional space?
What is the relationship between images and keywords in the multidimensional space?
What is the relationship between images and keywords in the multidimensional space?
