American Journal of Computer Science and Information Technology

Machine learning with spark

8^th Edition of International Conference on Big Data & Data Science
March 04-05, 2019 Barcelona, Spain

Plyushchenko Andrey N

Eastwind, Russia

Keynote: Am J Compt Sci Inform Technol

DOI: 10.21767/2349-3917-C1-007

Abstract

Spark 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 x2=x3. Internat. J. Algebra Comput. 21:973-1006.

Biography

Plyushchenko Andrey N has completed his PhD at Ural Federal University. 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 journals.

E-mail: a.plyushchenko@eastwind.ru