Machine Learning: Key Algorithms, Practical Applications, and Current Research Directions

International Journal of Electrical and Electronics Engineering

© 2025 by SSRG - IJEEE Journal

Volume 12 Issue 4

Year of Publication : 2025

Authors : Mohammad Nazmul Alam, Vijay Laxmi, Abhishek Sharma, Sarishma Dangi

10.14445/23488379/IJEEE-V12I4P102

How to Cite?

Mohammad Nazmul Alam, Vijay Laxmi, Abhishek Sharma, Sarishma Dangi, "Machine Learning: Key Algorithms, Practical Applications, and Current Research Directions," SSRG International Journal of Electrical and Electronics Engineering, vol. 12,  no. 4, pp. 12-46, 2025. Crossref, https://doi.org/10.14445/23488379/IJEEE-V12I4P102

Abstract:

We generate enormous amounts of data every day across various fields, such as finance, healthcare, sales, marketing, social media, and industry. State-of-the-art technology leverages this big data to make decisions and gain valuable insights. Machine learning, one of the most advanced and dynamic artificial intelligence techniques, utilizes large datasets to make predictions and develop intelligent applications. Machine learning algorithms enable computers to learn without being explicitly programmed. In this paper, we identify key algorithms and discuss fundamental algorithmic concepts. We explore various categories of machine learning, including supervised, unsupervised, semi-supervised, and reinforcement learning, along with their respective algorithms. Furthermore, we identify advanced machine learning applications across diverse fields. Finally, we discuss the challenges associated with machine learning techniques and potential future directions for developing algorithms and services.

Keywords:

Machine Learning, Reinforcement learning, Supervised, Unsupervised, Semi-supervised, Neural Network.

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