AI TECH MEETUP: Information-based approach (TICKET LINK IN DESCRIPTION!)

>> In order to attend this event as public you MUST get your ticket here: http://bit.ly/2iftbfw

>> AI TECH MEETUP is a series of meetings for those of you interested in Artificial Intelligence who have some tech background. Lectures will be both theoretical and hands-on. Supportive examples and exercises will be provided in R. Bring your laptop!!!

To attend this meetup you need at least basic knowledge of computer science, algorithms, analysis and algebra. Knowledge of R may be useful.

Whatever hot area you claim to work on (AI, cognitive science, ML, ect.) constructing a valid model that has forecast and adaptive capabilities is the task of utmost importance. This is the field with a overwhelming number of approaches, myths, spectacular successes and possibilites. And the field is burgeoning. Because of this richness and interdisciplinarity required to comprehend new developments it is very often very difficult to get speed up for aspiring technologist in this field. Hereby, we try to bridge this gap with a number of lectures.

>> The topic of the first lecture:
Information-based approach (idea, ID3, interpretability of decision tree, prunning, bagging, boosting, random forest, XGBoost) Held by Pawel Jakubas, PhD and CTO at Deep.BI (http://www.deep.bi/#) and Oksana Volnianska, PhD and Data Scientist at Deep.BI.

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