PAZUR 32 + WhyR + Analyx


Przewidujemy dwie prezentacje w języku angielskim.

1. Segmentation using NMF decomposition -- Marcin Kosiński
2. Efficient R programming: tips, tricks, and some interesting packages -- Adolfo Alvarez

Spotkanie odbędzie się w sali 003A (przyziemie, Gmach Główny UEP, Al. Niepodległości 10).

Spotkanie odbywa się w ramach cyku spotkań poprzedzających konferencję WhyR.


This pre-meeting promots
- Why R? 2019 Conference
- EARLY BIRD Registration
- Call for Papers

# Segmentation using NMF decomposition -- Marcin Kosiński

From the nowadays segmentation, we require them to follow below features:
- it should be balanced,
- segments should be distinctive,
- the discovered over and under indexed features within segments should create a meaningful story,
- and in the best case the amount of differentiative factors that drives segmentation should be small.

The last requirement often is a bottleneck in the scenario of a survey where respondents are asked enormous amount of questions.

The solution, one from many, to this use case can be the nonnegative matrix factorization that in a one attempt segments respondents and their features!

I'll present concept of the NMF decomposition and I'll present applications in R, with the explanation of diagnostic plots.

Working with high dimensional data? Often facing the need to group observations? That's a good presentation for you.

# Speakers bio

Marcin Kosiński has a master degree in Mathematical Statistics and Data Analysis specialty. Challenges seeker and devoted R language enthusiast. In the past, keen on the field of large-scale online learning and various approaches to personalized news article recommendation.
Community events host: organizer of Why R? conferences.
Interested in R packages development and survival analysis models. Currently explores and improves methods for quantitative marketing analyses and global surveys at Gradient Metrics.

Efficient R programming: tips, tricks, and some interesting packages -- Adolfo Alvarez

Learning R is a constant process, no matter if you are giving your first steps or you are already an R code star, there is always room to improve. In this talk we will try to agree on what is an efficient code, how to measure the efficiency of it, how to detect bottlenecks, and how to improve your code. Hopefully you will get some new ideas, packages or tricks you didn't know about!

Adolfo Alvarez is PhD in Business Management and Quantitative Methods, working as a data scientist in Analyx, and as adjunct professor in Collegium Da Vinci. His current main focus is to create, train, and develop data science teams.