Welcome to the advanced NLP topics section! Here, we dive deeper into complex concepts and practical applications. Let's explore together! 🚀

🔍 Key Concepts

  • Attention Mechanism
    The attention mechanism allows models to focus on relevant parts of input sequences.

    attention_mechanism

  • Transformer Models
    Transformers revolutionized NLP by leveraging self-attention layers.

    transformer_models

  • Sequence-to-Sequence (Seq2Seq)
    Seq2Seq frameworks are essential for tasks like machine translation.

    sequence_to_sequence

🧠 Practical Applications

  • Text Summarization
    Build models that compress long documents into concise summaries.

    text_summarization

  • Dialogue Systems
    Design chatbots that understand context and generate natural responses.

    dialogue_systems

  • Multilingual NLP
    Explore techniques for cross-lingual tasks and language transfer.

    multilingual_nlp

📚 Expand Your Knowledge

For foundational concepts, check out our NLP Basics Tutorial.
For advanced topics like BERT or GPT, visit Deep Learning in NLP.

Let me know if you'd like to dive into specific techniques! 🌐