01 - NLP Fundamentals: Tokenization, Embeddings and Transformers
Complete guide to NLP Fundamentals: Tokenization, Embeddings and Transformers: architecture, practical implementation and best practices for developers and technical teams.
Modern NLP: from BERT to LLMs
Modern NLP: BERT, GPT, transformers, subword tokenization, named entity recognition, sentiment analysis, machine translation, and information extraction with Hugging Face.
This series collects 10 articles (approximately 162 minutes of total reading time), designed for a level Advanced. The main topics covered are NLP, BERT, transformer, Hugging Face.
10Articles162 minTotal reading timeAdvancedLevel
NLPBERTtransformerHugging Facesentiment analysis
Series Articles
- 1
- 2
02 - BERT Explained: Architecture, Pretraining and Fine-tuning
Complete guide to BERT Explained: Architecture, Pretraining and Fine-tuning: architecture, practical implementation and best practices for developers and technical teams.
- 3
03 - Sentiment Analysis: Building and Deploying Classifiers
Complete guide to Sentiment Analysis: Building and Deploying Classifiers: architecture, practical implementation and best practices for developers and technical teams.
- 4
04 - Italian Sentiment Analysis: BERT Models and Challenges
Complete guide to Italian Sentiment Analysis: BERT Models and Challenges: architecture, practical implementation and best practices for developers and technical teams.
- 5
05 - Named Entity Recognition: Extracting Information from Text
Complete guide to Named Entity Recognition: Extracting Information from Text: architecture, practical implementation and best practices for developers and technical teams.
- 6
06 - Text Classification: Single and Multi-label Approaches
Complete guide to Text Classification: Single and Multi-label Approaches: architecture, practical implementation and best practices for developers and technical teams.
- 7
07 - HuggingFace Transformers: Models, Datasets, Training
Complete guide to HuggingFace Transformers: Models, Datasets, Training: architecture, practical implementation and best practices for developers and technical teams.
- 8
08 - Fine-tuning LLMs Locally: LoRA with 1 GPU
Complete guide to Fine-tuning LLMs Locally: LoRA with 1 GPU: architecture, practical implementation and best practices for developers and technical teams.
- 9
09 - Semantic Similarity: Measuring Text Relevance
Complete guide to Semantic Similarity: Measuring Text Relevance: architecture, practical implementation and best practices for developers and technical teams.
- 10
10 - Monitoring NLP: Detecting Drift and Scheduling Retraining
Complete guide to Monitoring NLP: Detecting Drift and Scheduling Retraining: architecture, practical implementation and best practices for developers and technical teams.
Test your knowledge!
Have you read all the articles? Check how much you've learned by taking this series' quizzes.