3.7 Neural Network and Deep Learning

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:

• The definition, historical overview and applications of Neural Network and Deep Learning
• Perceptron and Multi-Layer Perceptron (MLP) as the foundation of Neural Network
• PyTorch as a Deep Learning framework

Learners will be able to:

• Create and train a perceptron using NumPy
• Create and train an MLP / Fully Connected Neural Network using PyTorch
• Build a Fully Connected Neural Network model for classification using PyTorch

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: Introduction to Neural Networks and Deep Learning.
	1 HR MARK
30 mins	Code-along	Part 2: Perceptron and MLP.
10 mins	Break
20 mins	Code-along	Part 3: Introduction to PyTorch.
	2 HR MARK
50 mins	Code-along	Part 4: Building a Fully Connected Neural Network on MNIST and Titanic datasets.
10 mins	Briefing / Q&A	Brief on references, assignment, quiz and Q&A.
	END CLASS 3 HR MARK