AML AML Natural Language Processing & Computer Vision

Question 1

Which NLP technique converts words into dense vector representations that capture semantic relationships?

Accepted Answer

Word2Vec / Word Embeddings

Answer

TF-IDF

Answer

Bag of Words

Answer

Stemming

Question 2

What does TF-IDF stand for in text feature extraction?

Accepted Answer

Term Frequency–Inverse Document Frequency

Answer

Text Frequency–Inverse Document Function

Answer

Token Filter–Index Document Format

Answer

Text Format–Inverse Data Frame

Question 3

In computer vision, what is the role of a convolutional layer in a CNN?

Accepted Answer

Apply learnable filters to detect local spatial features

Answer

Flatten the image into a 1D vector

Answer

Normalize pixel values across channels

Answer

Perform non-maximum suppression on detected objects

Question 4

Which NLP task involves assigning a label (positive, negative, neutral) to a piece of text based on its emotional tone?

Accepted Answer

Sentiment Analysis

Answer

Named Entity Recognition

Answer

Machine Translation

Answer

Coreference Resolution

Question 5

What is the purpose of max pooling in a convolutional neural network?

Accepted Answer

Reduce spatial dimensions while retaining dominant features

Answer

Increase the spatial resolution of feature maps

Answer

Introduce non-linearity into the network

Answer

Normalize activations across the batch

Question 6

Which transformer-based model introduced bidirectional context for language understanding and set new NLP benchmarks in 2018?

Accepted Answer

BERT

Answer

GPT-2

Answer

ELMo

Answer

Seq2Seq