Covers: theory of Encoder-Decoder Model

- What is encoder- decoder network ?

Read chapter 11 section 11.2

Daniel Jurafsky

Sharvari Dhote**Total time needed: **~2 hours

- Learning Objectives
- Learn basics of sequence-to-sequence model and it's applications.
- Potential Use Cases
- It's applied to wide range of applications in Natural language processing include machine translation, summarization, question answering and dialogue.
- Target Audience
- BEGINNERData Scientist new to NLP

Go through the following **annotated items** *in order*:

BOOK_CHAPTER 1. Encoder-Decoder network explained

- What is encoder- decoder network ?

30 minutes

BOOK_CHAPTER 2. Introduction to recurrent neural network (RNN) language model

- What is RNN language model?

30 minutes

VIDEO 3. Recurrent Neural network language model

- What is recurrent neural network (RNN) and RNN's as Language Models?

30 minutes

ARTICLE 4. Encoder-decoder model application in machine translation

- How encoder-decoder is used in neural machine translation?

13 minutes

ARTICLE 5. Implement sequence-to-sequence model in Pytorch

- How to implement simple sequence to sequence machine translation model?

10 minutes

Previewing stream ** Natural Language Processing**

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