Module 1

This module focuses on the basics of Machine learning and the background knowledge required to understand and build TinyML applications. It answers the following questions:

• What is Machine Learning?

• What is TinyML?

• How to think of about a TinyML problem?

• What do you mean by Loss function?

• What is Gradient Descent?

• What are neurons?

• What is the difference between training and testing data?

• What are CNNs?

• How to work with images?

• What is responsible AI?

• Lecture 1
  • Introduction
  • Lecture 1
  • Lecture 1.1 -
  • Lecture 1.2
  • Lecture 1.3
  • Lecture 1.4
  • Lecture 1.5
  • Lecture 1.6
  • Lecture 1.7
  • Required Readings
• Lecture 2
  • Introduction
  • Lecture 2.1
  • Lecture 2.2
  • Lecture 2.3
  • Lecture 2.4
  • Lecture 2.5
  • Required Readings
• Lecture 3
  • Introduction
  • Lecture 3.1
  • Lecture 3.2
  • Lecture 3.3
  • Tutorials
  • Required Readings
• Lecture 4
  • Introduction
  • Lecture 4.1
  • Lecture 4.2
  • Lecture 4.3
  • Required Readings
• Lecture 5
  • Introduction
  • Lecture 5.1
  • Lecture 5.2
  • Lecture 5.3
  • Required Readings
• Lecture 6
  • Introduction
  • Lecture 6.1
  • Lecture 6.1
  • Lecture 6.2
  • Required Readings