A Comprehensive Review of Machine Learning Frameworks and Practical Applications
Ravi Bhushan1, Vineeta Khemchandani2
1Ravi Bhushan, School of Computer Science and Engineering. Galgotias University, Gr. Noida (Uttar Pradesh), India.
2Dr. Vineeta Khemchandani, School of Computer Applications and Technology, Galgotias University, Gr. Noida (Uttar Pradesh), India.
Manuscript received on 02 March 2026 | Revised Manuscript received on 09 March 2026 | Manuscript Accepted on 15 March 2026 | Manuscript published on 30 March 2026 | PP: 19-24 | Volume-15 Issue-4, March 2026 | Retrieval Number: 100.1/ijitee.E124215050426 | DOI: 10.35940/ijitee.E1242.15040326
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: A fundamental component of digitalisation solutions that have garnered significant attention in the digital sphere is machine learning, which is primarily an area of artificial intelligence. The author’s goal in this study is to provide a concise overview of the most widely utilised machine learning algorithms for this purpose. To assist in selecting the best learning algorithm to meet the application’s specific needs, the author aims to highlight the advantages and limitations of machine learning algorithms from the standpoint of their application. This paper provides a brief overview and outlook on the various uses of machine learning techniques.
Keywords: Machine Learning, Pseudo Code, Algorithm, Supervised Learning, Unsupervised Learning, Reinforcement Learning, ML Application and Task
Scope of the Article: Computer Science and Engineering