TensorFlow: Word Embeddings & Recurrent Neural Networks

TensorFlow    |    Intermediate
  • 11 Videos | 47m 28s
  • Includes Assessment
  • Earns a Badge
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Explore how to model language and text with word embeddings and how to use those embeddings in Recurrent Neural Networks. Leveraging TensorFlow to build custom RNN models is also covered.

WHAT YOU WILL LEARN

  • perform text to numeric conversion using one-hot encoding
    use frequency-based methods to generate word embeddings
    use name prediction-based methods to generate word embeddings
    identify pre-trained models for word vector embeddings
    describe how to work with recurrent neurons
  • recognize the construction of a recurrent neural networks by unrolling recurrent memory cells
    recognize the forward and backward passes while training a recurrent neural network
    compare long memory cells with the normal recurrent neuron
    "describe different kinds of encodings and why they are used "
    describe the working of recurrent neural networks and how they differ from regular neural networks

IN THIS COURSE

  • Playable
    1. 
    Course Overview
    2m 2s
    UP NEXT
  • Playable
    2. 
    One-Hot Encoding of Words
    5m 33s
  • Locked
    3. 
    Frequency-Based Encoding
    4m 5s
  • Locked
    4. 
    Prediction-Based Encoding
    4m 26s
  • Locked
    5. 
    Word2vec and GloVe Embeddings
    3m
  • Locked
    6. 
    Recurrent Neurons
    5m 54s
  • Locked
    7. 
    Unrolling a Recurrent Memory Cell
    2m 58s
  • Locked
    8. 
    Training a Recurrent Neural Network
    3m 54s
  • Locked
    9. 
    Long Memory Cells
    2m 47s
  • Locked
    10. 
    Exercise: Working with Word Encoding
    3m 41s
  • Locked
    11. 
    Exercise: Working with Recurrent Neural Networks
    4m 38s

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