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Sutapa Chattopadhyay

Bio: Sutapa Chattopadhyay is an academic researcher from St. Francis Xavier University. The author has contributed to research in topics: Deep learning & Machine learning. The author has co-authored 1 publications.

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Book ChapterDOI
20 Jun 2023
TL;DR: Predictive analytics, machine learning, and deep learning are inseparable as machine learning is used to automate predictive modeling to identify patterns, trends, or future outcomes as mentioned in this paper , which can use different machine learning techniques such as classifications, regressions, neural networks, clustering, and dimensionality reduction algorithms to create predictive models.
Abstract: Predictive analytics, machine learning, and deep learning are inseparable as machine learning, and deep learning algorithms are used to automate predictive modeling to identify patterns, trends, or future outcomes. We can use different machine learning and deep learning techniques such as classifications, regressions, neural networks, clustering, and dimensionality reduction algorithms to create predictive models. As a result, a business can now predict customers buying behavior, detect fraudulent activity, diagnose health care issues, recommend content, and predict machine maintenance needs. In a nutshell, predictive analytics created a revolution in all sectors such as finance, healthcare, retail, manufacturing, etc.