Introduction

⛓ 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)

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