A Comprehensive Overview of Machine Learning Models: Techniques, Applications, and Future Directions

Author(s)	Mr. Aravind Puppala
Country	United States
Abstract	Machine learning (ML) is an integral part of modern computational systems, driving innovations in various industries ranging from healthcare to finance. This article provides an in-depth exploration of the most widely used machine learning models, categorizing them into supervised, unsupervised, and reinforcement learning paradigms. The paper discusses the underlying theory of each model, presents real-world applications, and highlights challenges, advancements, and future research directions in machine learning. With the rapid evolution of AI, this article also reflects on emerging trends and the growing need for transparency and ethical considerations in model development and deployment.
Keywords	ML,Supervised, unsupervised
Field	Computer Applications
Published In	Volume 7, Issue 2, March-April 2025
Published On	2025-04-05
DOI	https://doi.org/10.36948/ijfmr.2025.v07i02.40603
Short DOI	https://doi.org/g9dg5q

About IJFMR Fees & Payment Current Issue Publication Archive	Submit Research Paper Track Submission Status Publication Guidelines Publication Ethics Peer Review & Plagiarism	Join as a Reviewer Editors & Reviewers Reviewer Referral Program Get Reviewer Membership Certi.	Website/Journal Policies Usage Policy Content Policies Privacy Policy

Contact Us		+91-9687-828-838	editor@ijfmr.com

International Journal For Multidisciplinary Research