Machine Learning & AI Camp

CAMP OUTLINE

Before the camp (Homework)

1. Study and solve the notebook Introduction to Python, Google Colab and Jupyter Notebook

2. Study and solve the notebook Recap: Functions, Lines, Parabolas

3. Study and complete projects in the micro:bit Resources for Learners section of the Coding using micro:bit - I page.

Note: you can also complete the projects using the micro:bit simulator. That is, you don’t need the hardware device to do these projects. Similarly, the section ‘At the Camp’ provides alternative exercises using the online simulator in case you don’t have the hardware.

4. Complete Quiz 0.

At the camp (days 1 and 2)

1. Linear regression

   • micro:bit data logger

   • Linear regression with micro:bit

   • Exercise: complete the Fahrenheit thermometer project using Python and the micro:bit simulator. Explain how this problem can be solved with the linear regression model.

2. Logistic regression

   • Logistic regression with micro:bit

   • Exercise: complete the Compass North project using Python and the micro:bit simulator. Explain how this problem can be solved with the logistric regression model.

3. Classifying XOR. MLP

   • A Neural Network Playground

4. Quiz 1

5. Classifying real datasets: Iris and MNIST

6. Convolutional Neural Networks

   • micro:bit – projecting digits.

   • Online students: TBD.

After the camp

1. Quiz 2