title: Ð Ð°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ° Ð¸ Ð°Ð²ÑÐ¾Ð¼Ð°ÑÐ¸Ð·Ð°ÑÐ¸Ñ Ð¼Ð¾Ð´ÐµÐ»Ð¸ Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð´Ð»Ñ Ð¿ÑÐµÐ´ÑÐºÐ°Ð·Ð°Ð½Ð¸Ñ Ð²ÑÐ¶Ð¸Ð²Ð°ÐµÐ¼Ð¾ÑÑÐ¸ ÐºÐ»Ð¸ÐµÐ½ÑÐ¾Ð² ÐºÐ¾Ð¼Ð¼ÐµÑÑÐµÑÐºÐ¾Ð³Ð¾ Ð¿ÑÐµÐ´Ð¿ÑÐ¸ÑÑÐ¸Ñ
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¼Ð°Ð³Ð¸ÑÑÑÐ°
titleType: Subtitle
Creators: name: ÐÐ½Ð°ÑÑÐº, ÐÐ³Ð¾ÑÑ
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2020
Subjects: ÐÑÑÐ¸ÑÐ»Ð¸ÑÐµÐ»ÑÐ½ÑÐµ Ð¼Ð°ÑÐ¸Ð½Ñ ÑÐ»ÐµÐºÑÑÐ¾Ð½Ð½ÑÐµ
ÑÐ°ÑÐ¿ÑÐµÐ´ÐµÐ»ÐµÐ½Ð½Ð°Ñ Ð¾Ð±ÑÐ°Ð±Ð¾ÑÐºÐ°
Ð±Ð¾Ð»ÑÑÐ¸Ðµ Ð´Ð°Ð½Ð½ÑÐµ
Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ
Ð³Ð»ÑÐ±Ð¾ÐºÐ¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ

description: ÐÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¼Ð°Ð³Ð¸ÑÑÑÐ° Ð¿Ð¾ÑÐ²ÑÑÐµÐ½Ð°
ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐºÐµ Ð¸ Ð°Ð²ÑÐ¾Ð¼Ð°ÑÐ¸Ð·Ð°ÑÐ¸Ð¸ Ð¼Ð¾Ð´ÐµÐ»Ð¸ Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð´Ð»Ñ
Ð¿ÑÐµÐ´ÑÐºÐ°Ð·Ð°Ð½Ð¸Ñ Ð²ÑÐ¶Ð¸Ð²Ð°ÐµÐ¼Ð¾ÑÑÐ¸ ÐºÐ»Ð¸ÐµÐ½ÑÐ° ÐºÐ¾Ð¼Ð¼ÐµÑÑÐµÑÐºÐ¾Ð³Ð¾ Ð¿ÑÐµÐ´Ð¿ÑÐ¸ÑÑÐ¸Ñ.
Ð ÑÐ¾Ð´Ðµ Ð¿ÑÐ¾Ð²ÐµÐ´ÐµÐ½Ð¸Ñ ÑÐ°Ð±Ð¾ÑÑ Ð±ÑÐ»Ð° Ð¾Ð±ÑÑÐµÐ½Ð° Ð¸ Ð°Ð²ÑÐ¾Ð¼Ð°ÑÐ¸Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ð°
Ð¼Ð¾Ð´ÐµÐ»Ñ Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð¿ÑÐ¸ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸Ð¸ ÑÐ¾Ð²ÑÐµÐ¼ÐµÐ½Ð½ÑÑ
Ð¿ÐµÑÐµÐ´Ð¾Ð²ÑÑ ÑÐµÑÐ½Ð¾Ð»Ð¾Ð³Ð¸Ð¹ Ð±Ð¾Ð»ÑÑÐ¸Ñ Ð´Ð°Ð½Ð½ÑÑ, Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð¸
Ð³Ð»ÑÐ±Ð¾ÐºÐ¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ. Ð ÑÐ¾Ð¼Ñ Ð¶Ðµ, Ð±ÑÐ»Ð¸ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ñ ÑÐ¾Ð²ÑÐµÐ¼ÐµÐ½Ð½ÑÐµ
Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ñ Ð¿Ð¾ÑÑÑÐ¾ÐµÐ½Ð¸Ñ Ð²ÐµÐºÑÐ¾ÑÐ½Ð¾Ð³Ð¾ Ð¿ÑÐµÐ´ÑÑÐ°Ð²Ð»ÐµÐ½Ð¸Ñ Ð´Ð°Ð½Ð½ÑÑ Ð´Ð»Ñ
ÑÐ»ÑÑÑÐµÐ½Ð¸Ñ ÐºÐ°ÑÐµÑÑÐ²Ð° Ð¼Ð¾Ð´ÐµÐ»Ð¸. ÐÐ° Ð¾ÑÐ½Ð¾Ð²Ðµ Ð¾Ð±Ð·Ð¾ÑÐ° Ð´ÑÑÐ³Ð¸Ñ ÑÐ¾Ð²ÑÐµÐ¼ÐµÐ½Ð½ÑÑ
Ð¼ÐµÑÐ¾Ð´Ð¾Ð² Ð¸ ÑÑÐ°Ð²Ð½ÐµÐ½Ð¸Ñ ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÐ¾Ð² Ð½Ð° Ð¿ÑÐ°ÐºÑÐ¸ÐºÐµ Ð±ÑÐ» Ð²ÑÐ±ÑÐ°Ð½ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼
Node2Vec.
ÐÐ±ÑÑÐµÐ½Ð½Ð°Ñ Ð¼Ð¾Ð´ÐµÐ»Ñ Ð¿ÐµÑÐµÐ´Ð°ÐµÑÑÑ Ð½Ð° ÐºÐ»Ð°ÑÑÐµÑÐµ Apache Hadoop, Ð³Ð´Ðµ
Ð²ÑÑÐ¸ÑÐ»ÑÑÑÑÑ Ð¿ÑÐµÐ´ÑÐºÐ°Ð·Ð°Ð½Ð¸Ð¹ Ð² Ð±Ð¾Ð»ÑÑÐ¸Ñ Ð¾Ð±ÑÐµÐ¼Ð°Ñ Ð¿ÑÐ¸ Ð¿Ð¾Ð¼Ð¾ÑÐ¸ Apache
Spark.
Ð ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÐµ, Ð¼Ð¾Ð´ÐµÐ»Ñ Ð±ÑÐ»Ð° Ð¾Ð±ÑÑÐµÐ½Ð° Ð¸ Ð¿ÑÐ¾ÑÐµÑÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð°,
Ð¿ÑÐ¾Ð´ÐµÐ¼Ð¾Ð½ÑÑÑÐ¸ÑÐ¾Ð²Ð°Ð² ÑÐ¾ÑÐ¾ÑÐµÐµ ÐºÐ°ÑÐµÑÑÐ²Ð¾ Ð¿ÑÐµÐ´ÑÐºÐ°Ð·Ð°Ð½Ð¸Ð¹. ÐÐ²ÑÐ¾Ð¼Ð°ÑÐ¸Ð·Ð°ÑÐ¸Ñ
Ð¿ÑÐ¾Ð¸ÑÑÐ¾Ð´Ð¸Ð»Ð° Ñ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸ÐµÐ¼ Apache Airflow Ð½Ð° ÐºÐ»Ð°ÑÑÐµÑÐµ Hadoop.
description: The master thesis is devoted to development and automation of the
machine learning model for predicting business customer survival.
In the course of the work, the machine learning model was fitted
and automated using modern technologies of big data, machine learning
and deep learning. In addition, modern algorithms for constructing a vector
representation of data were used to improve the quality of the model. Based
on the comparative analysis, the Node2Vec algorithm was chosen.
The fitted model is sent to the Apache Hadoop cluster, where large-
scale predictions are calculated using Apache Spark.
As a result, the model was fitted and tested, demonstrating the good
quality of the predictions. Automation took place using Apache Airflow on
a Hadoop cluster.