/    /  NLP- Interview questions Part 6

1. What are word embedding libraries ? 

Answer: Word embedding libraries are as follows;

1. Word2vec

2. Glove

3. Fasttext

4. Genism

 

2. What is word2vec ? 

Answer: Word2vec is a group of related models that are used to produce word embeddings. They are shallow, two-layer neural network models that are trained to reconstruct linguistic contexts of words.

 

3. What is Glove ? 

Answer: GloVe, coined from Global Vectors, is a model for distributed word representation. They are unsupervised learning algorithm model for obtaining vector representations for words. Hence, this is achieved by mapping words into a meaningful space where the distance between words is related to semantic similarity.

 

4. What is Fasttext ? 

Answer:  fastText is a library for learning of word embeddings and text classification created by Facebook’s AI Research lab. This allows to create an unsupervised learning or supervised learning algorithm model for obtaining vector representations for words

 

5. What is Genism ?

Answer: It is a production-ready open-source library for unsupervised topic modeling and natural language processing, using modern statistical machine learning. Gensim is implemented in Python and Cython for top performance and scalability.