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American Journal of Computer Science and Information Technology
ISSN: 2349-3917
March 04-05, 2019
Barcelona, Spain
Big Data 2019
Page 16
8
th
Edition of International Conference on
Big Data &
Data Science
S
park is the one of the most popular tools for effective
Big Data manipulation with high-level languages such
as Python, Scala, etc. PySpark is a Python-library for spark
using. Although Spark includes a library of machine learning
algorithms, the most popular local machine libraries such as
SKLearn, XGBoost, etc., are more flexible and give the best
results. We describe some techniques, which allow fitting
standard algorithms and predicting values for distributed
data.
Recent Publications
1. A N Plyushchenko and A M Shur (2011) Almost
overlap-free words and the word problem for the
free Burnside semigroup satisfying x
2
=x
3
. Internat. J.
Algebra Comput. 21:973-1006.
Biography
Plyushchenko Andrey N has completed his PhD at Ural Federal Universi-
ty. He has completed School of Data Analysis at Yandex. Currently, he is
a Head of Data Science Department in Eastwind, Software Development
Company. He works with projects related to machine learning, Big Data,
Data Analysis, etc. He has published about eight papers in reputed jour-
nals.
a.plyushchenko@eastwind.ruKey no
Machine learning with spark
Plyushchenko Andrey N
Eastwind, Russia
Plyushchenko Andrey N, Am J Compt Sci Inform Technol 2019, Volume 7
DOI: 10.21767/2349-3917-C1-007