Artificial intelligence

Presentation & objectives

The objective of session 5 in this programming block is to discover more advanced concepts in artificial intelligence. In the practical activity, you will implement a machine learning model using the scikit-learn library and object-oriented programming.

Before the class

Prior knowledge acquisition

To do this session, you need to have finished the non-optional activities of algo session 6 (artificial intelligence), in particular you need a functional implementation of the $k$-nearest neighbors algorithm.

Technical requirements

To be able to start working on the activity, you should meet the following requirements:

• Please bring your own computer.
• Make sure to have a functional network connection.

Course contents

To be able to start the practical activity efficiently, we will introduce some needed concepts at the beginning of the class. To save you some time, we will present you a few slides, that you can find hereafter:

• Slides of the session.

These slides only cover the main elements of the course, and many more details are given in the associated articles. Thus, you should study the following articles at home after the session:

• OOP and ML using sklearn.
• Model ensembling.
• Hyperparameters tuning.

You can verify your understanding of these articles here:

• Self-assessment quiz.

Practical activity

The rest of the class is dedicated to a practical activity. When ready, click on the link below to start:

• Practical activity.

After the class

Complete the current session

Before the next session, you should:

• Review the contents of the articles above.
• Complete the non-optional parts of the practical activity.