• Tarandeep Kaur
• Harjinder Kaur

Abstract: Machine learning is the most prevailing and predominant tool that is being used for extraction and reveling of knowledge from huge amount of data. Most of the machine learning research has been focusing on improvements in the accurateness and effectiveness of training and inference algorithms. There are several important components of machine learning depending upon the type of output, input, features and learning being used. This paper explores the variable components of machine learning with an exhaustive analysis into the sub-components as well. It explores the different types of learning methods in machine learning whilst listing the challenges posed in accomplishing the problem solving through the use of statistical methods or machine learning algorithms.

Keywords: Supervised learning, Reinforcement learning, Pattern matching, Artificial Intelligence

"Machine Learning: An Internal Review ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 11, page no.248-253, November 2018, Available :http://www.jetir.org/papers/JETIRDS06037.pdf

"Machine Learning: An Internal Review ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 11, page no. pp248-253, November 2018, Available at : http://www.jetir.org/papers/JETIRDS06037.pdf