Advancements in Machine Learning Algorithms for Predictive Analytics

Authors

  • Cutter Smith Scholar, Burto College

Keywords:

Machine learning, Predictive analytics, Supervised learning, Reinforcement learning

Abstract

Advancements in machine learning algorithms and their applications in predictive analytics. We review state-of-the-art techniques such as deep learning, ensemble methods, and reinforcement learning, highlighting their strengths and limitations in various domains. Our analysis focuses on the mathematical principles underlying these algorithms and their practical implications for data-driven decision-making and problem-solving.

References

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Data Mining, Inference, and Prediction. Springer.

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Press.

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Deep Learning with Python, scikit-learn, and TensorFlow. Packt Publishing.

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Published

13-03-2024

How to Cite

Cutter Smith. (2024). Advancements in Machine Learning Algorithms for Predictive Analytics. Journal of Applied Optics, 159–164. Retrieved from https://appliedopticsjournal.net/index.php/JAO/article/view/98

Issue

Section

Conference Paper

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