⛓ ‍Basics of Sequence Models

⛓ Sequence Models In General

  • Sequences are data structures where each example could be seen as a series of data points, for example 🧐:

  • Since we have labeled data X and Y so all of these tasks are addressed as Supervised Learning 👩‍🏫

  • Even in Sequence-to-Sequence tasks lengths of input and output can be different ❗

🤔 Why Do We Need Sequence Models?

  • Machine learning algorithms typically require the text input to be represented as a fixed-length vector 🙄

  • Thus, to model sequences, we need a specific learning framework able to:

    • ✔ Deal with variable-length sequences

    • ✔ Maintain sequence order

    • ✔ Keep track of long-term dependencies rather than cutting input data too short

    • ✔ Share parameters across the sequence (so not re-learn things across the sequence)

👩‍💻 My Codes

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