Course detail

Machine Learning

FEKT-MPC-MLRAcad. year: 2020/2021

Students will gain insight into advanced machine learning methods. They will be able to describe and compare the properties of individual approaches to data classification. They will be able to select and apply a specific approach to a given problem. They will also gain practical experience with current implementations of machine learning methods.

Learning outcomes of the course unit

Not applicable.

Prerequisites

Not applicable.

Co-requisites

Not applicable.

Recommended optional programme components

Not applicable.

Recommended or required reading

Holčík, J. Analýza a klasifikace dat, Akademické nakladatelství CERM, 2012 (CS)
Komprdová, K. Rozhodovací stromy a lesy, Akademické nakladatelství CERM, 2012 (CS)
Buduma N. Fundamentals of Deep Learning, O'Reilly Media, 2017 (CS)

Planned learning activities and teaching methods

Not applicable.

Assesment methods and criteria linked to learning outcomes

Not applicable.

Language of instruction

Czech

Work placements

Not applicable.

Aims

Not applicable.

Classification of course in study plans

  • Programme MPC-BIO Master's, 2. year of study, winter semester, 5 credits, compulsory
  • Programme MPC-BTB Master's, 2. year of study, winter semester, 5 credits, compulsory

Type of course unit

 

Exercise in computer lab

26 hours, compulsory

Teacher / Lecturer

eLearning