3.10 Natural Language Processing Advanced

Dependencies

Refer to the following markdown file for the respective sections of the class:

• Self Studies
• Lesson
• Assignment
• Quiz
• Reference

Lesson Objectives

Learners will understand:

• Deep Learning for NLP
• Common NLP tasks
• Recurrent Neural Networks (RNN)
• Attention Mechanism
• Transformers

Learners will be able to:

• Train an RNN for language modeling
• Fine-tune a pre-trained BERT model for sentiment analysis
• Use a pre-trained BERT model for NER
• Use a pre-trained GPT-2 model for text generation

Lesson Plan

Duration	What	How or Why
- 5mins	Start zoom session	So that learners can join early and start class on time.
20 mins	Activity	Recap on self-study and prework materials.
40 mins	Code-along	Part 1: Deep Learning for NLP and common NLP tasks.
	1 HR MARK
30 mins	Code-along	Part 2: RNNs- LSTM and GRU.
10 mins	Break
20 mins	Code-along	Part 3: Attention mechanism.
	2 HR MARK
50 mins	Code-along	Part 4: Transformers- BERT and GPT.
10 mins	Briefing / Q&A	Brief on references, assignment, quiz and Q&A.
	END CLASS 3 HR MARK