Bohdan Pavlyshenko

11 Abonné

6 SlideShares 11 Abonné

6 SlideShares 11 Abonné

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...

time series predictive analytics text mining forecasting data mining business intelligence nlp bayesian inference logistic regression xgboost failure detection. stock market prediction trends predicition natural language processing big data

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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...

time series predictive analytics text mining forecasting data mining business intelligence nlp bayesian inference logistic regression xgboost failure detection. stock market prediction trends predicition natural language processing big data

Tout plus