Abstract

  The future of any business from banking, e-commerce, real estate, homeland security, healthcare, marketing, the stock market, manufacturing, education, retail to government organizations depends on the data and analytics capabilities that are built and scaled. The speed of change in technology in recent years has been a real challenge for all businesses. To manage that, a significant number of organizations are exploring the Big Data (BD) infrastructure that helps them to take advantage of new opportunities while saving costs. As necessity of any business to be resilience, one needs Forecasting with a paradigm that fits to that business day-to-day operation using their incoming daily and timely information-driven by those data while comparing them with existing historical data to do Data Analytics (DA) and Data Predictive (DP) which will be derivative the observation of these data. Give the speed of incoming in real-time at sheer volume, leave us no choice but using Artificial Intelligence (AI) and consequently Machine Learning (ML) as its foundation and together with Deep Learning (DL) will enhance our predictive analytic to be to augment a forecasting model into our business to make it more resilience. In this article, we discuss these topics.

Keywords:Artificial Intelligence; Machine Learning; Deep Learning; Resilience System; Forecasting and Related Paradigm; Big Data; Fuzzy Logic

References

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Citation

Citation: Bahman Zohuri., et al. “Machine Learning Driving Forecasting Paradigm". Acta Scientific Computer Sciences 2.3 (2020): 19-23.