NLP

Fundamentals

• Language AI
• NLP Pipeline
• Text Representation
• Tokenization
• Embedding
• Transformer

Tasks

• Text Classification
• Intent Detection
• Named Entity Recognition
• Summarization
• Text Generation
• Topic Modeling
• Semantic Search

Few/No Label Learning

• Few-shot Learning
• Zero-shot Classification
• Intent Detection
• Data Augmentation
• Semi-supervised Learning

Summarization And Evaluation

• Text Summarization Pipelines
• Measuring the Quality of Generated Text
• Summarization Baseline
• Comparing Different Summaries
• ROUGE
• BLEU
• PEGASUS

Token-Level Learning

• Tokenization to NER Label Alignment
• Multilingual NER Workflow
• Tokenizing Texts for NER
• Performance Measures for NER
• Error Analysis for NER

Multilingual NLP

• Multilingual Transformer
• SentencePiece
• Cross-Lingual Transfer
• Zero-shot Learning
• Fine-Tuning XLM-RoBERTa

Sources

• Natural Language Processing with Transformers
• Practical Natural Language Processing
• NLP Transformers - Chapter 03 - Transformer Anatomy
• NLP Transformers - Chapter 04 - Multilingual Named Entity Recognition
• NLP Transformers - Chapter 06 - Summarization
• NLP Transformers - Chapter 09 - Dealing with Few to No Labels
• Practical NLP - Chapter 02 - NLP Pipeline
• Practical NLP - Chapter 03 - Text Representation
• Practical NLP - Chapter 11 - The End-to-End NLP Process

Questions

• How Do Positional Embeddings Scale Context Length