Getting Started with Google BERT

Explore Google BERT, fine-tune NLP tasks, discover variants, and build real-world applications with cutting-edge transformer models.

Intermediate

120 Lessons

25h

Certificate of Completion

Explore Google BERT, fine-tune NLP tasks, discover variants, and build real-world applications with cutting-edge transformer models.

AI-POWERED

Explanations

AI-POWERED

Explanations

This course includes

26 Playgrounds

12 Quizzes

This course includes

26 Playgrounds

12 Quizzes

Course Overview

This comprehensive course dives into Google’s BERT architecture, exploring its revolutionary role in natural language processing (NLP). Starting with BERT’s architecture and pre-training methods, you’ll uncover the mechanics of transformers, including encoder-decoder components and self-attention mechanisms. Gain hands-on experience fine-tuning BERT for NLP tasks like sentiment analysis, question-answering, and named entity recognition. Discover BERT variants such as ALBERT, RoBERTa, and DistilBERT alongsi...Show More

TAKEAWAY SKILLS

Transformer Models

Machine Learning

What You'll Learn

An understanding of Google BERT’s architecture, pre-training tasks (MLM, NSP), and transformer fundamentals like self-attention and multi-head attention

The ability to apply and fine-tune pretrained BERT models for NLP tasks such as sentiment analysis, NER, question answering, and domain-specific applications

Familiarity with BERT variants (ALBERT, RoBERTa, ELECTRA) and lightweight models using knowledge distillation (DistilBERT, TinyBERT)

The ability to utilize advanced BERT applications, including text summarization (BERTSUM), multilingual models (M-BERT), and multimodal tools like VideoBERT

The ability to build real-world projects using BERT libraries like Hugging Face Transformers and apply domain-specific models like BioBERT and FinBERT

What You'll Learn

An understanding of Google BERT’s architecture, pre-training tasks (MLM, NSP), and transformer fundamentals like self-attention and multi-head attention

Course Content

Before We Start

Get familiar with Google's BERT architecture for NLP tasks and fine-tuning methods.

About the Course

Starting Off with BERT

Look at BERT’s architecture, pre-training tasks, and applications in NLP tasks.

Introduction: BERT

A Primer on Transformers

Work your way through the transformer architecture, including encoder-decoder components and self-attention mechanisms.

Introduction to the Transformer Understanding the Encoder of the Transformer Self-Attention Mechanism Understanding the Self-Attention Mechanism Multi-Head Attention Mechanism Learning Position with Positional Encoding Encoder: Feedforward and Add and Norm Component Putting All the Encoder Components Together Understanding the Decoder of the Transformer Masked Multi-Head Attention Multi-Head Attention Decoder: Feedforward and Add and Norm Component Putting All the Decoder Components Together Putting the Encoder and Decoder Together Summary: A Primer on Transformers Exercise: A Primer on Transformers Exercise: Decoder Architecture Quiz: A Primer on Transformers

Understanding the BERT Model

Grasp the fundamentals of the BERT model's architecture, training, and tokenization methods.

Introduction to the BERT Model Working of BERT Configurations of BERT Pre-Training the BERT Model The WordPiece Tokenizer Pre-Training Strategies for the BERT Model Masked Language Modeling Next Sentence Prediction Pre-Training Procedure Subword Tokenization Algorithms Byte Pair Encoding Byte-Level Byte Pair Encoding and WordPiece Algorithms Summary: Understanding the BERT Model Quiz: Understanding the BERT Model

Getting Hands-On with BERT

Solve problems in applying pre-trained BERT for various NLP tasks using embeddings.

Exploring the Pre-Trained BERT Model Transformers Extracting Embeddings From All Encoder Layers of BERT Fine-Tuning BERT for Downstream Tasks Sentiment Analysis Natural Language Inference Question-Answering Performing Question-Answering with the Fine-Tuned BERT Named Entity Recognition Summary: Getting Hands-On with BERT Quiz: Getting Hands-On with BERT

Exploring BERT Variants

1 Lesson

Focus on notable BERT variants and their architectural enhancements for efficient performance.

Different BERT Variants

12 Lessons

Practice using ALBERT, RoBERTa, ELECTRA, and SpanBERT for task-specific NLP improvements.

BERT Variants—Based on Knowledge Distillation

14 Lessons

Try out knowledge distillation in BERT variants, including DistilBERT and TinyBERT.

Applications of BERT

1 Lesson

Look at BERT's diverse applications in text summarization, multilingual tasks, and specialized fields.

10.

Exploring BERTSUM for Text Summarization

8 Lessons

Examine text summarization and fine-tuning BERTSUM for extractive and abstractive summaries.

Semantic Search with Transformers

Project

11.

Applying BERT to Other Languages

18 Lessons

Grasp the fundamentals of utilizing multilingual and monolingual BERT models in various languages.

12.

Exploring Sentence and Domain-Specific BERT

10 Lessons

Dig into Sentence-BERT enhancements and domain-specific adaptations like ClinicalBERT and BioBERT.

13.

Working with VideoBERT, BART, and More

10 Lessons

See how VideoBERT integrates video and language, and explore BART's text, document summation.

14.

Conclusion

1 Lesson

Approach Google BERT for state-of-the-art NLP applications and innovative projects.

Similarity Detection in English Language Using RoBERTa

Project

Course Author

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