English

Analytics of Business Time Series Using Machine Learning and Bayesian Inference

Machine Learning 2022-06-03 v2

Abstract

In the survey we consider the case studies on sales time series forecasting, the deep learning approach for forecasting non-stationary time series using time trend correction, dynamic price and supply optimization using Q-learning, Bitcoin price modeling, COVID-19 spread impact on stock market, using social networks signals in analytics. The use of machine learning and Bayesian inference in predictive analytics has been analyzed.

Keywords

Cite

@article{arxiv.2205.12905,
  title  = {Analytics of Business Time Series Using Machine Learning and Bayesian Inference},
  author = {Bohdan M. Pavlyshenko},
  journal= {arXiv preprint arXiv:2205.12905},
  year   = {2022}
}

Comments

Survey article. arXiv admin note: text overlap with arXiv:2201.02034, arXiv:2201.02058, arXiv:2201.02729, arXiv:2201.02049, arXiv:2004.01489

R2 v1 2026-06-24T11:28:40.827Z