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Quiz Part IV: Applications and Advanced Techniques
Chapter 13: Project: Sentiment Analysis Dashboard
- 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
- Which model is an example of a deep learning approach to sentiment analysis?
- A) Logistic Regression
- B) Naive Bayes
- C) LSTM
- D) Decision Tree
- 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
- 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
Chapter 13: Project: Sentiment Analysis Dashboard
- 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
- Which model is an example of a deep learning approach to sentiment analysis?
- A) Logistic Regression
- B) Naive Bayes
- C) LSTM
- D) Decision Tree
- 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
- 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
Chapter 13: Project: Sentiment Analysis Dashboard
- 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
- Which model is an example of a deep learning approach to sentiment analysis?
- A) Logistic Regression
- B) Naive Bayes
- C) LSTM
- D) Decision Tree
- 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
- 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
Chapter 13: Project: Sentiment Analysis Dashboard
- 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
- Which model is an example of a deep learning approach to sentiment analysis?
- A) Logistic Regression
- B) Naive Bayes
- C) LSTM
- D) Decision Tree
- 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
- 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