TensorFlow: Sentiment Analysis with Recurrent Neural Networks

TensorFlow    |    Intermediate
  • 12 Videos | 57m 33s
  • Includes Assessment
  • Earns a Badge
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Discover how to construct neural networks for sentiment analysis. How to generate word embeddings on training data and use pre-trained word vectors for sentiment analysis is also covered.

WHAT YOU WILL LEARN

  • install TensorFlow and work with Jupyter notebooks
    demonstrate how to load and explore training data
    identify how to pre-process data to feed into the neural network
    create unique identifiers to represent individual words in the vocabulary
    create a neural network for sentiment analysis
    describe how to train the neural network for prediction
  • identify how to pre-process data to feed into the neural network with pre-trained word vectors
    create a lookup table to map words to unique identifiers
    specify training data sentences in the form of word identifiers
    perform sentiment analysis using GloVe embeddings
    recall how RNNs can be used for sentiment analysis

IN THIS COURSE

  • Playable
    1. 
    Course Overview
    1m 27s
    UP NEXT
  • Playable
    2. 
    Configuring the TensorFlow Environment
    2m 9s
  • Locked
    3. 
    Training Data
    3m 36s
    FREE ACCESS
  • Locked
    4. 
    Data Pre-Processing
    6m 12s
    FREE ACCESS
  • Locked
    5. 
    Unique Identifiers to Represent Words
    6m 27s
    FREE ACCESS
  • Locked
    6. 
    Construct a Recurrent Neural Network
    8m 51s
    FREE ACCESS
  • Locked
    7. 
    Training the Neural Network
    6m 26s
    FREE ACCESS
  • Locked
    8. 
    Data Pre-Processing to Use Pre-Trained Word Vectors
    2m 22s
    FREE ACCESS
  • Locked
    9. 
    Lookup Table to Map Unique Identifiers
    5m 40s
    FREE ACCESS
  • Locked
    10. 
    Sentences Using Word Identifiers
    4m 54s
    FREE ACCESS
  • Locked
    11. 
    Sentiment Analysis Using Pre-Trained Vectors
    6m 44s
    FREE ACCESS
  • Locked
    12. 
    Exercise: Performing Sentiment Analysis
    2m 45s
    FREE ACCESS

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