Top 10 NLP Concepts Interview Questions and Answers | Machine Learning | Deep Learning
Natural Language Processing (NLP) terminologies are frequently asked during data science and machine learning interviews. In this tutorial, we will talk about the top 10 Natual Language Processing (NLP) concepts interview questions and how to answer them. The top 10 questions are:
👉 1. What are vocabularies, documents, and corpus in NLP?
👉 2. What is tokenization?
👉 3. What are stop words?
👉 4. What is N-gram?
👉 5. What are stemming and lemmatization?
👉 6. What is count vectorization?
👉 7. What is TF-IDF?
👉 8. What is bag of words?
👉 9. What is word embedding?
👉 10. What are word2vec, CBOW, and skip-gram?
⏰ Timecodes ⏰
0:00 - Intro
0:15 - Question 1: What are vocabularies, documents, and corpus in NLP?
0:47 - Question 2: What is tokenization?
1:18 - Question 3: What are stop words?
2:22 - Question 4: What is N-gram?
3:05 - Question 5: What are stemming and lemmatization?
3:30 - Question 6: What is count vectorization?
4:18 - Question 7: What is TF-IDF?
6:16 - Question 8: What is bag of words (BoW)?
6:40 - Question 9: What is word embedding?
7:14 - Question 10: What are word2vec, CBOW, and skip-gram?
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