A Comprehensive Review of Machine Learning and Data Science Applications: From Fundamentals to Advanced Techniques

Abstract

Machine learning and data science have become integral to various fields, from healthcare and finance to autonomous vehicles and natural language processing. This paper provides a comprehensive review of the fundamental and advanced techniques in machine learning, covering a range of topics from basic algorithms to deep learning architectures and generative models. We discuss the historical development, key concepts, and applications of these techniques, highlighting their significance in modern data-driven applications. By understanding both foundational and advanced concepts, researchers and practitioners can develop more effective and innovative machine learning applications.