Скачать или смотреть Natural Language Processing with Transformers | Book Summary

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In this video, we summarize “Natural Language Processing with Transformers,” a hands-on guide to building state-of-the-art NLP systems using Transformer architectures.

This book bridges theory and practice, showing how models like BERT, GPT, T5, and RoBERTa power modern language understanding and generation.

🔥 What you’ll learn in this summary:
Why Transformers replaced RNNs and CNNs in NLP
How self-attention works and why it scales
Pretraining, fine-tuning, and transfer learning for NLP
Using Hugging Face Transformers for real-world projects
NLP tasks: classification, NER, QA, summarization, and generation
Evaluation, bias, hallucinations, and ethical considerations
Deploying Transformer-based NLP systems in production

Whether you're an ML engineer, NLP practitioner, or AI enthusiast, this summary provides a clear, practical overview of modern NLP.

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