Advanced NLP: Introduction to BERT

Natural Language Processing    |    Intermediate
  • 12 videos | 1h 14m 8s
  • Includes Assessment
  • Earns a Badge
Rating 4.3 of 6 users Rating 4.3 of 6 users (6)
In every domain of artificial intelligence, there is one algorithm that transforms the entire field into an industry-matured tool to be used across a broad spectrum of use cases. BERT is that algorithm for natural language processing (NLP). In this course, explore the fundamentals of BERT architecture, including variations, transfer learning capabilities, and best practices. Examine the Hugging Face library and its role in sentiment analysis problems. Practice model setup, pre-processing, sentiment classification training, and evaluating models using BERT. Finally, take a critical look to recognize the challenges of using BERT. Upon completing this course, you'll be able to demonstrate how to solve simple sentiment analysis problems.

WHAT YOU WILL LEARN

  • Discover the key concepts covered in this course
    Outline bidirectional encoder representations from transformers (bert) architecture and its applications
    Distinguish between different types of bert models
    Recognize bert transfer learning approaches
    Define the hugging face library and outline its benefits
    Perform library, model setup, and data exploration
  • Perform data pre-processing and bert tokenization
    Perform sentiment classification training with bert and hugging face
    Perform model evaluation and predicting sentiment for raw text
    Outline best practices to use for bert modelling
    List bert challenges and deployment strategies
    Summarize the key concepts covered in this course

IN THIS COURSE

  • 1m 23s
  • 14m 47s
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    3.  Types of BERT Models
    4m 56s
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    4.  Transfer Learning with BERT
    5m 27s
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    5.  The Hugging Face Ecosystem
    4m 20s
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    6.  Practicing Model Setup & Data Exploration with BERT
    7m 29s
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    7.  Pre-processing Data with BERT
    10m 10s
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    8.  Using BERT for Sentiment Classification Training
    13m 47s
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    9.  Evaluating Models with BERT
    5m 18s
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    10.  Best Practices for BERT
    2m 46s
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    11.  BERT Challenges and Deployment Strategy
    2m 46s
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    12.  Course Summary
    59s

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