Skip to ContentGo to accessibility pageKeyboard shortcuts menu
OpenStax Logo
Principles of Data Science

Chapter Review

Principles of Data ScienceChapter Review
1.
What is the primary role of hidden layers in a neural network?
  1. To directly interact with the input data and produce the final output
  2. To provide a way for the network to learn and represent complex patterns and relationships within the data
  3. To reduce the number of features of the input data
  4. To store the final predictions of the model
2.
What is a convolutional neural network (CNN), and in which scenarios might it perform better than standard neural networks?
  1. A CNN is a type of neural network designed to process sequential data, and it is particularly effective for tasks like language translation and text generation.
  2. A CNN is a type of neural network that includes recurrent layers, making it suitable for time series prediction and speech recognition.
  3. A CNN is a type of neural network that uses convolutional layers to process grid-like data structures, such as images, and is particularly effective for tasks like image classification, object detection, and recognizing spatial relationships.
  4. A CNN is a type of neural network that relies on decision trees, and it is particularly effective for classification tasks involving structured tabular data.
3.
Why are speech recognition and text-to-speech algorithms important in everyday life, and what are some examples of their applications?
  1. Speech recognition and text-to-speech algorithms are mainly used in scientific research and have limited everyday applications.
  2. These algorithms are only relevant in the context of language translation and have no significant impact on everyday life.
  3. Speech recognition is primarily used for recording audio, while text-to-speech is used mainly for entertainment purposes, such as audiobooks.
  4. These algorithms are important because they enable hands-free interaction with devices, improve accessibility for individuals with disabilities, and enhance user experience in various applications.
4.
Which of the following would be considered an unethical use of AI or NLP technology?
  1. Developing a chatbot that provides customer service and technical support on a 24/7 basis
  2. Creating a natural language processing system that assists visually impaired users in reading text aloud
  3. Designing a virtual assistant that collects personal data without explicit user consent and sells it to third-party advertisers
  4. Implementing an AI-based language model that translates content across different languages for educational purposes
PreviousNext
Citation/Attribution

This book may not be used in the training of large language models or otherwise be ingested into large language models or generative AI offerings without OpenStax's permission.

Want to cite, share, or modify this book? This book uses the Creative Commons Attribution-NonCommercial-ShareAlike License and you must attribute OpenStax.

Attribution information
  • If you are redistributing all or part of this book in a print format, then you must include on every physical page the following attribution:
    Access for free at https://openstax.org/books/principles-data-science/pages/1-introduction
  • If you are redistributing all or part of this book in a digital format, then you must include on every digital page view the following attribution:
    Access for free at https://openstax.org/books/principles-data-science/pages/1-introduction
Citation information

© Dec 19, 2024 OpenStax. Textbook content produced by OpenStax is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike License . The OpenStax name, OpenStax logo, OpenStax book covers, OpenStax CNX name, and OpenStax CNX logo are not subject to the Creative Commons license and may not be reproduced without the prior and express written consent of Rice University.