Getting Started with Google BERT
Explore Google BERT, fine-tune NLP tasks, discover variants, and build real-world applications with cutting-edge transformer models.
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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
Learning Roadmap
3.
A Primer on Transformers
A Primer on Transformers
18 Lessons
18 Lessons
4.
Understanding the BERT Model
Understanding the BERT Model
14 Lessons
14 Lessons
5.
Getting Hands-On with BERT
Getting Hands-On with BERT
11 Lessons
11 Lessons
7.
Different BERT Variants
Different BERT Variants
12 Lessons
12 Lessons
8.
BERT Variants—Based on Knowledge Distillation
BERT Variants—Based on Knowledge Distillation
14 Lessons
14 Lessons
10.
Exploring BERTSUM for Text Summarization
Exploring BERTSUM for Text Summarization
8 Lessons
8 Lessons
11.
Applying BERT to Other Languages
Applying BERT to Other Languages
18 Lessons
18 Lessons
12.
Exploring Sentence and Domain-Specific BERT
Exploring Sentence and Domain-Specific BERT
10 Lessons
10 Lessons
13.
Working with VideoBERT, BART, and More
Working with VideoBERT, BART, and More
10 Lessons
10 Lessons
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