Natural Language Processing with Python Updated EditionChapter 175
Chapter 13: Project: Sentiment Analysis Dashboard
Section 5 of 7-~ 1 min read-Synced from Cuantum content
1. What is the goal of sentiment analysis? - A) To categorize text into different topics
- B) To determine the emotional tone behind a body of text
- C) To translate text from one language to another
- D) To generate a summary of a text
1. Which model is an example of a deep learning approach to sentiment analysis? - A) Logistic Regression
- B) Naive Bayes
- C) LSTM
- D) Decision Tree
1. Why is it important to handle imbalanced data in sentiment analysis? - A) To increase the dataset size
- B) To ensure the model does not favor the majority class
- C) To simplify the preprocessing steps
- D) To reduce the computational cost
1. What is the purpose of data visualization in the sentiment analysis dashboard? - A) To preprocess text data
- B) To create machine learning models
- C) To help users understand the sentiment analysis results more effectively
- D) To store the analysis results