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X Summer School

Achievements and Applications
of Contemporary Informatics, Mathematics and Physics
August 4-18, 2015, Kyiv (Ukraine)

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Introduction to Machine Learning

Introduction to Machine Learning

Abstract:

The course offers a gentle, hands-on introduction to the core principles and techniques of machine learning. The participants will be presented with the basic supervised machine learning models (linear models, trees and some instance-based techniques), along with the principles of their application (training, testing, cross-validation, regularization, model selection). Students will implement and apply most of the discussed algorithms using the interactive environment IPython. This will be followed by a discussion of the general principles underlying machine learning, such as statistical estimation methods and optimization techniques. Some extent of basic familiarity with programming and Python is expected from the participants. Previous knowledge of probability theory and linear algebra would be helpful and could ensure better understanding of the material.

About lecturer:

Mr. Konstantin Tretyakov,
Researcher, University of Tartu, Estonia.


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  • About us
    • What is AACIMP?
    • Organizers
    • Contact us
    • Kyiv
  • Partners
    • How to get involved
    • Financial
    • Media
    • Corporate Sponsorship
    • Travel
    • In kind
  • Program
    • Smart Cities
    • 3D Printing
    • Computational Neuroscience
    • Applied Computer Science
    • Poster Session
    • Plenary Session
    • Student Projects
    • AACIMP 2013
    • AACIMP 2014
  • Participation
    • General schedule
    • How to apply?
    • Eligible students
    • Student responsibilities
  • Tuition
    • Registration fees
    • How to pay?
    • Discounts & scholarships
  • Housing
    • Accommodation
    • Dining services
    • Travel information
    • Visa information
  • Impressions
    • Photo memories
    • Video memories
    • Organizers impressions
    • Alumni opinions
  • Promotion
  • FAQ