Experiment -1 MCQ's
1.Which two libraries are commonly used for Word Analysis in Natural Language Processing?
- a) TensorFlow and Keras
- b) NLTK and spaCy
- c) Pandas and NumPy
- d) Matplotlib and Seaborn
2.What is the purpose of the
word_tokenizefunction in NLTK?- a) It extracts named entities from the text.
- b) It converts sentences into words or tokens.
- c) It identifies Part-of-Speech tags for each word.
- d) It performs sentiment analysis on the text.
3.Which library is known for its speed and efficiency in Natural Language Processing?
- a) TensorFlow
- b) NLTK
- c) spaCy
- d) Gensim
4.Which command is used to load the English language model in spaCy?
- a)
spacy.load("en_core_web_sm") - b)
spacy.init("en_core_web_sm") - c)
load_model("en_core_web_sm") - d)
initialize_model("en_core_web_sm")
- a)
5.What does the
pos_tagfunction in NLTK do?- a) Tokenizes the text into words or phrases.
- b) Extracts named entities from the text.
- c) Assigns Part-of-Speech tags to words.
- d) Performs lemmatization on the text.
6.Which step is necessary in Google Colab if NLTK is not pre-installed?
- a) Import
nltkusing!pip install nltk - b) Import
spacyusing!pip install spacy - c) Import
word_tokenizeusing!pip install word_tokenize - d) Import
nltkusing!apt-get install nltk
- a) Import
7.What does the code snippet
tokens = [token.text for token in doc]do in spaCy?- a) Generates POS tags for each token in the text.
- b) Retrieves tokens or words from the processed document.
- c) Performs sentiment analysis on the text.
- d) Tokenizes the text using NLTK.
44 Comments
21471A4344
ReplyDelete1b) NLTK and spaCy
2b) It converts sentences into words or tokens.
3c) spaCy
4a) spacy.load("en_core_web_sm")
5c) Assigns Part-of-Speech tags to words.
6a) Import nltk using !pip install nltk
7b) Retrieves tokens or words from the processed document.
1-b
ReplyDelete2-b
3-c
4-a
5-c
6-a
7-b
1-b
ReplyDelete2-b
3-c
4-a
5-c
6-a
7-b
1-b
ReplyDelete2-b
3-c
4-a
5-c
6-a
7-b
thank you all
Delete21471A4317
ReplyDelete1) b
2) b
3) c
4) a
5) c
6) a
7) b
21471A4327
ReplyDelete1b) NLTK and spaCy
2b) It converts sentences into words or tokens.
3c) spaCy
4a) spacy.load("en_core_web_sm")
5c) Assigns Part-of-Speech tags to words.
6a) Import nltk using !pip install nltk
7b) Retrieves tokens or words from the processed document.
21471A4322
ReplyDelete1:-B
2:-B
3:-C
4:-A
5:-C
6:-A
7:-B
21471A4339
ReplyDelete1)b
2)b
3)c
4)a
5)c
6)a
7)b
21471A4350
ReplyDelete1.b
2.b
3.c
4.a
5.c
6.a
7.b
1-b
ReplyDelete2-b
3c
4-a
5-c
6-a
7-b
21471A4347
ReplyDelete1b) NLTK and spaCy
2b) It converts sentences into words or tokens.
3c) spaCy
4a) spacy.load("en_core_web_sm")
5c) Assigns Part-of-Speech tags to words.
6a) Import nltk using !pip install nltk
7b) Retrieves tokens or words from the processed document.
21471A4329
ReplyDelete1)b
2)b
3)c
4)a
5)c
6)a
7)b
21471A4342
ReplyDelete1)b
2)b
3)c
4)a
5)c
6)a
7)b
1) b
ReplyDelete2) b
3) c
4) a
5) c
6) a
7) b
21471A4307
ReplyDelete1)b
2)b
3)c
4)a
5)c
6)a
7)b
21471A4326
ReplyDelete1)B
2)B
3)C
4)A
5)C
6)A
7)B
1-b
ReplyDelete2-b
3-c
4-a
5-c
6-a
7-b
Very good
Delete21471A4346
ReplyDelete1)b
2)b
3)c
4)a
5)c
6)a
7)b
21471A4324
ReplyDelete1b) NLTK and spaCy
2b) It converts sentences into words or tokens.
3c) spaCy
4a) spacy.load("en_core_web_sm")
5c) Assigns Part-of-Speech tags to words.
6a) Import nltk using !pip install nltk
7b) Retrieves tokens or words from the processed document.
21471A4341
ReplyDelete1)B
2)B
3)C
4)A
5)C
6)A
7)B
21471A4358
ReplyDelete1.b
2.b
3.c
4.a
5.c
6.a
7.b
ReplyDelete1b) NLTK and spaCy
2b) It converts sentences into words or tokens.
3c) spaCy
4a) spacy.load("en_core_web_sm")
5c) Assigns Part-of-Speech tags to words.
6a) Import nltk using !pip install nltk
7b) Retrieves tokens or words from the processed document.
21471A4306
ReplyDelete1b) NLTK and spaCy
2b) It converts sentences into words or tokens.
3c) spaCy
4a) spacy.load("en_core_web_sm")
5c) Assigns Part-of-Speech tags to words.
6a) Import nltk using !pip install nltk
7b) Retrieves tokens or words from the processed document.
21471A4319
ReplyDelete1.b) NLTK and spaCy
2.b) It converts sentences into words or tokens.
3.c) spaCy
4.a) spacy.load("en_core_web_sm")
5.c) Assigns Part-of-Speech tags to words.
6.a) Import nltk using !pip install nltk
7.b) Retrieves tokens or words from the processed document.
21471A4321
ReplyDelete1-b
2-b
3-c
4-a
5-c
6-a
7-b
21471A4361
ReplyDelete1b) NLTK and spaCy
2b) It converts sentences into words or tokens.
3c) spaCy
4a) spacy.load("en_core_web_sm")
5c) Assigns Part-of-Speech tags to words.
6a) Import nltk using !pip install nltk
7b) Retrieves tokens or words from the processed document.
21471A4349
ReplyDelete1b) NLTK and spaCy
2b) It converts sentences into words or tokens.
3c) spaCy
4a) spacy.load("en_core_web_sm")
5c) Assigns Part-of-Speech tags to words.
6a) Import nltk using !pip install nltk
7b) Retrieves tokens or words from the processed document
1b) NLTK and spaCy
ReplyDelete2b) It converts sentences into words or tokens.
3c) spaCy
4a) spacy.load("en_core_web_sm")
5c) Assigns Part-of-Speech tags to words.
6a) Import nltk using !pip install nltk
7b) Retrieves tokens or words from the processed document
21471A4352
ReplyDelete1)b
2)b
3)c
4)a
5)c
6)a
7)b
21471A4332
ReplyDelete1b) NLTK and spaCy
2b) It converts sentences into words or tokens.
3c) spaCy
4a) spacy.load("en_core_web_sm")
5c) Assigns Part-of-Speech tags to words.
6a) Import nltk using !pip install nltk
7b) Retrieves tokens or words from the processed document.
21471A4365
ReplyDelete1b) NLTK and spaCy
2b) It converts sentences into words or tokens.
3c) spaCy
4a) spacy.load("en_core_web_sm")
5c) Assigns Part-of-Speech tags to words.
6a) Import nltk using !pip install nltk
7b) Retrieves tokens or words from the processed document
1-b
ReplyDelete2-b
3-c
4-a
5-c
6-a
7-b
1-b
ReplyDelete2-b
3-c
4-a
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7-b
1-b
ReplyDelete2-b
3-c
4-a
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1-b
ReplyDelete2-b
3-c
4-a
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6-a
7-b
21471A4328
ReplyDelete1-b
2-b
3-c
4-a
5-c
6-a
7-b
1-B
ReplyDelete2-B
3-C
4-A
5-C
6-A
7-B
1 b
ReplyDelete2 b
3 c
4 a
5 c
6 a
7 b
21471A4303
ReplyDelete21471A4343
ReplyDelete21471A4331
ReplyDelete1.b
2.b
3.c
4.a
5.c
6.a
7.b
21471A4316
ReplyDelete1-b [ NLTK and spaCy]
2-b [ it converts sentences into words or tokens.
3-c[ spaCy]
4-a [spaCy.load('en_core_web_sm')
5-c [ Assign part of speech tags to words]
6-a [ import nltk using !pip install nltk ]
7-b [ retrieves tokens or words from the processed document ]