AI Practitioner: Practical BERT Examples

Artificial Intelligence    |    Expert
  • 16 videos | 50m 7s
  • Includes Assessment
  • Earns a Badge
Rating 4.1 of 7 users Rating 4.1 of 7 users (7)
Bidirectional Encoder Representations from Transformers (BERT) can be implemented in various ways, and it is up to AI practitioners to decide which one is the best for a particular product. It is also essential to recognize all of BERT's capabilities and its full potential in NLP. In this course, you'll outline the theoretical approaches to several BERT use cases before illustrating how to implement each of them. In full, you'll learn how to use BERT for search engine optimization, sentence prediction, sentence classification, token classification, and question answering, implementing a simple example for each use case discussed. Lastly, you'll examine some fundamental guidelines for using BERT for content optimization.

WHAT YOU WILL LEARN

  • Discover the key concepts covered in this course
    Name practical approaches to improving search using bert
    Describe how bert functions inside a search engine
    Demonstrate how bert can be used to search the text of a given document
    Describe how we can use bert for next sentence prediction
    Use bert and python for next sentence prediction via a pytorch implementation of bert
    Outline how bert can be used for sequence classification
    Work with bert to implement a sequence classifier
  • Describe how multiple-choice reading comprehension can be done using bert
    Use bert and python to implement multiple choice examples via a pytorch implementation of bert
    Outline how to utilize bert for token classification
    Work with bert to implement a token classifier
    Describe how to develop a question-answering machine using bert
    Work with bert to implement a question-answering machine
    Outline some fundamental guidelines for content optimization using bert
    Summarize the key concepts covered in this course

IN THIS COURSE

  • 2m 36s
  • 3m 40s
    After completing this video, you will be able to name practical approaches to improving search using BERT. FREE ACCESS
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    3.  How BERT is Used in Searches
    2m 34s
    Upon completion of this video, you will be able to describe how BERT functions inside of a search engine. FREE ACCESS
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    4.  Implementing a Mini Search Engine Using BERT
    3m 28s
    In this video, you will learn how BERT can be used to search the text of a given document. FREE ACCESS
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    5.  BERT for Next Sentence Prediction
    2m 51s
    After completing this video, you will be able to describe how we can use BERT for next sentence prediction. FREE ACCESS
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    6.  Using BERT and Python for Next Sentence Prediction
    3m 52s
    In this video, you will learn how to use BERT and Python for next sentence prediction. FREE ACCESS
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    7.  BERT for Sequence Classification
    3m 35s
    In this video, you will outline how BERT can be used for sequence classification. FREE ACCESS
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    8.  Implementing a Sequence Classifier Using BERT
    3m 41s
    In this video, you will work with BERT to implement a sequence classifier. FREE ACCESS
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    9.  BERT for Multiple Choice
    3m 30s
    After completing this video, you will be able to describe how to do multiple-choice reading comprehension using BERT. FREE ACCESS
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    10.  Using BERT and Python for Multiple Choice
    4m 8s
    Find out how to use BERT and Python to implement multiple choice examples via a PyTorch implementation of BERT. FREE ACCESS
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    11.  BERT for Token Classification
    2m 34s
    In this video, you will outline how to use BERT for token classification. FREE ACCESS
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    12.  Implementing Token Classification Using BERT
    2m 49s
    In this video, you will learn how to work with BERT to implement a token classifier. FREE ACCESS
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    13.  BERT for Question Answering
    3m 26s
    After completing this video, you will be able to describe how to develop a question-answering machine using BERT. FREE ACCESS
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    14.  Implementing Question-answering Machines Using BERT
    3m 7s
    In this video, you will work with BERT to implement a question-answering machine. FREE ACCESS
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    15.  Guidelines for Content Optimization Using Bert
    3m 6s
    Find out how to outline some fundamental guidelines for content optimization using BERT. FREE ACCESS
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    16.  Course Summary
    1m 12s
    In this video, we will summarize the key concepts covered in this course. FREE ACCESS

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