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Codeless Deep Learning with KNIME

You're reading from  Codeless Deep Learning with KNIME

Product type Book
Published in Nov 2020
Publisher Packt
ISBN-13 9781800566613
Pages 384 pages
Edition 1st Edition
Languages
Authors (3):
Kathrin Melcher Kathrin Melcher
Profile icon Kathrin Melcher
KNIME AG KNIME AG
Rosaria Silipo Rosaria Silipo
Profile icon Rosaria Silipo
View More author details

Table of Contents (16) Chapters

Preface 1. Section 1: Feedforward Neural Networks and KNIME Deep Learning Extension
2. Chapter 1: Introduction to Deep Learning with KNIME Analytics Platform 3. Chapter 2: Data Access and Preprocessing with KNIME Analytics Platform 4. Chapter 3: Getting Started with Neural Networks 5. Chapter 4: Building and Training a Feedforward Neural Network 6. Section 2: Deep Learning Networks
7. Chapter 5: Autoencoder for Fraud Detection 8. Chapter 6: Recurrent Neural Networks for Demand Prediction 9. Chapter 7: Implementing NLP Applications 10. Chapter 8: Neural Machine Translation 11. Chapter 9: Convolutional Neural Networks for Image Classification 12. Section 3: Deployment and Productionizing
13. Chapter 10: Deploying a Deep Learning Network 14. Chapter 11: Best Practices and Other Deployment Options 15. Other Books You May Enjoy

Questions and Exercises

  1. What is a word embedding?

    a) An encoding functionality that can be trained within the neural network

    b) A text cleaning procedure

    c) A training algorithm for an RNN

    d) A postprocessing technique to choose the most likely character

  2. Which statement regarding sentiment analysis is true?

    a) Sentiment analysis can only be solved with RNNs.

    b) Sentiment analysis is the same as emotion detection.

    c) Sentiment analysis identifies the underlying sentiment in a text.

    d) Sentiment analysis is an image processing task.

  3. What does a many-to-many architecture mean?

    a) An architecture with an input sequence and an output sequence

    b) An architecture with an input sequence and a vector as output

    c) An architecture with many hidden units and many outputs

    d) An architecture with one input feature and an output sequence

  4. Why do I need a trigger sequence for free text generation?

    a) To calculate the probabilities

    b) To compare the prediction with the target

    c) To initialize the...

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