Advanced NLP: Language Translation Using Transformer Model

Natural Language Processing    |    Intermediate
  • 13 videos | 1h 29m 12s
  • Includes Assessment
  • Earns a Badge
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Translating from one language to another is a common task in Natural Language Processing (NLP). The transformer model works by passing multiple words through a neural network simultaneously and is one of the newest models propelling a surge of progression, sometimes referred to as transformer AI. In this course, you will solve real-world machine translation problems, translating from English to French. Explore machine translation problem formulation, notebook setup, and data pre-processing. Then, learn to tokenize and vectorize data into a sequence of integers, where each integer represents the index of a word in a vocabulary. Discover transformer encoder-decoder and see how to produce input and output sequences. Finally, define the attention layer and assemble, train, and evaluate the translation model end to end. Upon completing this course, you will be able to solve industry-level problems using deep learning methodology in the TensorFlow ecosystem.

WHAT YOU WILL LEARN

  • Discover the key concepts covered in this course
    Outline machine translation applications
    Demonstrating english to french machine translation - frame a problem and use single sentence translation
    Demonstrating english to french machine translation - set up the environment and download the translation data
    Demonstrating english to french machine translation - perform exploratory data analysis (eda) and data pre-processing
    Demonstrating english to french machine translation - use tokens and vectors in integer sequences
    Demonstrating english to french machine translation - define training and validation datasets with input, target of specified batch size, and sequence length
  • Demonstrating english to french machine translation - produce a new representation of input sequence using transformer encoder
    Demonstrating english to french machine translation - produce an output target sequence using transformer decoder
    Demonstrating english to french machine translation - define attention and positional embedding for input sequence
    Demonstrating english to french machine translation - assemble and train model end to end
    Demonstrating english to french machine translation - translate a test sentence using a trained model
    Summarize the key concepts covered in this course

IN THIS COURSE

  • 1m 22s
  • 8m 10s
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    3.  Using Single Sentence English to French Translation
    2m 17s
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    4.  Setting up the Environment for Translation
    5m 36s
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    5.  Performing EDA for Translation
    3m 39s
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    6.  Using Tokens and Vectors for Translation
    4m 48s
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    7.  Using Training and Validation Data for Translation
    14m 56s
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    8.  Using Transformer Encoder for Translation
    9m 15s
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    9.  Using Transformer Decoder for Translation
    11m 35s
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    10.  Defining Attention and Embedding for Translation
    5m 20s
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    11.  Assembling and Training the Model for Translation
    10m 6s
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    12.  Using a Trained Model for Translation
    11m 19s
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    13.  Course Summary
    48s

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