2023/2024
Modern Data Analysis: Machine Learning
Type:
Mago-Lego
Delivered by:
Big Data and Information Retrieval School
When:
1 module
Online hours:
52
Open to:
students of one campus
Language:
English
ECTS credits:
3
Contact hours:
10
Course Syllabus
Abstract
In this course, students are introduced to the main types of machine learning problems. Simple and multiple linear regression, evaluation of the quality of the obtained models, interpretation of the importance of features are considered. The solution of the classification problem is also discussed: algorithms such as Logistic Regression, Support Vector Machine and Decision Trees are considered. In addition, students gain insight into model ensembles.
Learning Objectives
- Get familiar with the basic machine learning definitions
- Understand such concepts as overfitting and regularization
- Understand how gradient descent works and how it is used in machine learning
- Know which models are used to solve regression and classification tasks
- Be able to use the scikit-learn library to train machine learning models
Expected Learning Outcomes
- Get familiar with the basic machine learning definitions
- Understand how gradient descent works and how it is used in machine learning.
- Understand such concepts as overfitting and regularization.
- Know which models are used to solve regression and classification tasks.
- Be able to use the scikit-learn library to train machine learning models.
