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Summer School of Research Methods – Forecasting, Machine self-learning and AI

This June Data Science Society is presenting to you the Summer School of Research Methods! We are involved in the action and will be able to provide you with exclusive videos from the lectures and workshops. If you are interested in Forecasting, Machine self-learning and AI this is a great opportunity for you to grab some awesome materials on the topics presented by our experts.

This June Data Science Society is presenting to you the Summer School of Research Methods! We are involved in the action and will be able to provide you with exclusive videos from the lectures and workshops. If you are interested in Forecasting, Machine self-learning and AI this is a great opportunity for you to grab some awesome materials on the topics presented by our experts.

Sign up here for the event and expect the videos to be distributed to you around July. πŸ™‚

Link to register for the post event materials:Β  https://www.datasciencesociety.net/events/summer-school-of-research-methods-forecasting-machine-self-learning-and-ai/

ATTENTION: You must understand the Bulgarian language to watch these videos.

Summer School of Research Methods
20-24 June 2018

Main objectives:
Creating an attitude to study and apply research methods in research.
Winning the hearts and minds of learners to apply the scientific method.
Permanent change of student attitudes.

Concept: Intensive training through methods through lectures, workshops.

Lecturers:
Angel Marchev Sr.
Alexander Efremov
Kaloyan Haralampiev
Marian Milev
Stanimir Kabaivanov
Boryana Bogdanova
Boyan Lomev
Angel Marchev ml.
Pavel Nikolov

Introduction
– Opening Session: Angel Marchev, Senior General Systems Theory, Systemic Approach to Research

Forecasting
– Angel Marchev, PhD – Cybernetics for the Study of Complex Systems with Feedback
– Marian Milev: An Introduction to Probability Theory
– Workshop: Boryana Bogdanova: Analysis and forecasting of time series

Machine self-learning
– Alexander Efremov: Data mining – methods and basic tasks
– Kaloyan Haralampiev: Methods and tools for data analysis
– Workshop: Alexander Efremov / Kaloyan Haralampiev – Data Mining

AI
– Stanimir Kabaivanov: Methods for Neural Network Modeling
– Angel Marchev, ml. – Multi-choice selection procedure
– Workshop: Pavel Nikolov – a case of artificial intelligence (including work in virtualized environment)

Conclusions
– Peter Nikolov: Quantum calculations

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