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BohdanPavlyshenko

Bohdan Pavlyshenko

6 際際滷Shares11 Followers
6 際際滷Shares11 Followers
Personal Information
Organization / Workplace
Ukraine Ukraine
Occupation
Data Analyst at SoftServe
Industry
Technology / Software / Internet
Website
http://bpavlyshenko.blogspot.com
About
Master level at Kaggle (https://www.kaggle.com/bpavlyshenko) My current scientific areas are: Data Mining, Predictive Analytics, Machine Learning, Information Retrieval, Text Mining, Natural Language Processing, R Analytics, Social Network Analysis, Big Data; semantic field approach in the analysis of semi-structured data; semantic approach in machine learning algorithms of classification and clusterization of text documents; analysis of social network informational streams; the use of the theories of formal concept analysis and frequent sets in the data mining of semi-structured data, particularly text streams; the use of numerical characteristics of frequent sets and association rules...
Contact Details

Presentations(6)油

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Using Consolidated Tabular and Text Data in Business Predictive Analytics
Using Consolidated Tabular and Text Data in Business Predictive AnalyticsUsing Consolidated Tabular and Text Data in Business Predictive Analytics
Using Consolidated Tabular and Text Data in Business Predictive Analytics
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Linear, Machine Learning or Probabilistic Predictive Models: What's Best for Time Series Forecasting and Failure Detection?
Linear, Machine Learning or Probabilistic Predictive Models: What's Best for Time Series Forecasting and Failure Detection?Linear, Machine Learning or Probabilistic Predictive Models: What's Best for Time Series Forecasting and Failure Detection?
Linear, Machine Learning or Probabilistic Predictive Models: What's Best for Time Series Forecasting and Failure Detection?
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Linear, Machine Learning and Probabilistic Approaches for Predictive Analytics
Linear, Machine Learning and Probabilistic Approaches for Predictive AnalyticsLinear, Machine Learning and Probabilistic Approaches for Predictive Analytics
Linear, Machine Learning and Probabilistic Approaches for Predictive Analytics
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