Advancements in AI/ML Algorithms and their Integration with Data Science for Enhanced Decision-Making and Automation
DOI:
https://doi.org/10.26438/ijcse/v12i12.2532Keywords:
Data Systems Design, Data Development, Business Intelligence (BI), Artificial Intelligence (AI), Machine Learning (ML)Abstract
This article delves into the rapid advancements in AI/ML algorithms and their integration with data science practices to drive enhanced decision-making and automation. Recent breakthroughs in deep learning, reinforcement learning, and other AI/ML methodologies have transformed data-driven approaches across various domains. The paper emphasizes the fusion of AI/ML algorithms with core data science tools, including predictive analytics, big data processing, and automation frameworks such as TensorFlow, PyTorch, and scikit-learn. Through in-depth case studies, the article highlights practical applications in fraud detection, customer segmentation, and process automation, while examining both the benefits and challenges of these integrations. Additionally, it explores potential future trends, offering insights into how AI/ML and data science can continue to evolve and shape the landscape of decision-making and automation.
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