Enhancing Predictive Analytics in Cloud-Based Environments Using Machine Learning Algorithms

EasyChair Preprint 14993

Abstract

The integration of machine learning (ML) algorithms within cloud computing environments has revolutionized predictive analytics, providing scalable and efficient solutions for handling vast datasets. This paper explores the deployment of advanced ML techniques in cloud environments to enhance predictive analytics. We analyze the performance of various ML models, including neural networks, decision trees, and support vector machines, in cloud-based systems. Our findings demonstrate significant improvements in processing speed, scalability, and predictive accuracy, offering valuable insights for industries relying on real-time data analytics. The paper also addresses the challenges of implementing ML in cloud environments, such as latency, data security, and model optimization, proposing strategies to overcome these issues.

Keyphrases: Artificial Intelligence, Big Data, Cloud Computing, Data Science, Predictive Analytics, machine learning

@booklet{EasyChair:14993,
  author    = {Sophia Müller},
  title     = {Enhancing Predictive Analytics in Cloud-Based Environments Using Machine Learning Algorithms},
  howpublished = {EasyChair Preprint 14993},
  year      = {EasyChair, 2024}}