AI Practitioner: Practical BERT Examples
Artificial Intelligence
| Expert
- 16 Videos | 57m 7s
- Includes Assessment
- Earns a Badge
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
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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
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1.Course Overview2m 36sUP NEXT
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2.Search Improvement Using BERT3m 40s
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3.How BERT is Used in Searches2m 34s
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4.Implementing a Mini Search Engine Using BERT3m 28s
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5.BERT for Next Sentence Prediction2m 51s
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6.Using BERT and Python for Next Sentence Prediction3m 52s
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7.BERT for Sequence Classification3m 35s
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8.Implementing a Sequence Classifier Using BERT3m 41s
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9.BERT for Multiple Choice3m 30s
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10.Using BERT and Python for Multiple Choice4m 8s
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11.BERT for Token Classification2m 34s
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12.Implementing Token Classification Using BERT2m 49s
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13.BERT for Question Answering3m 26s
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14.Implementing Question-answering Machines Using BERT3m 7s
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15.Guidelines for Content Optimization Using Bert3m 6s
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16.Course Summary1m 12s
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