This is an old revision of the document!
Lab 10 - Machine Learning
Objectives
Understand basic concepts of machine learning
Remember examples of real-world problems that can be solved with machine learning
Learn the most common performance evaluation metrics for machine learning models
Analyse the behaviour of typical machine learning algorithms using the most popular techniques
Be able to compare multiple machine learning models
Resources
The exercises will be solved in Python, using various popular libraries that are usually integrated in machine learning projects:
Scikit-Learn: fast model development, performance metrics, pipelines, dataset splitting
Pandas: data frames, csv parser, data analysis
NumPy: scientific computation
-
Classification Dataset
Regression dataset
Tasks
Google Colab Notebook
For this lab, we will use Google Colab for exploring performance evaluation in machine learning. Please solve your tasks here by clicking โOpen in Colaboratoryโ.
You can then export this python notebook as a PDF (File โ Print) and upload it to Moodle.