A Simplistic Overview of Machine Learning
DOI:
https://doi.org/10.32628/IJSRSET218475Keywords:
Machine Learning, Supervised, Unsupervised, reinforcement, decision tree.Abstract
While dealing with machine learning, a computer learns first to perform a roles/task by learning a set of training examples. The computer performs then the same task along with data it hasn't found before. This paper presents a brief overview of machine-learning types along with instances. The paper also covers differences between supervised and unsupervised learning.
References
- Inza, I., Calvo, B., Armañanzas, R., Bengoetxea, E., Larrañaga, P., & Lozano, J. Machine learning: an indispensable tool in bioinformatics. In Bioinformatics methods in clinical research (pp. 25-48), Humana Press, 2010.
- K.P. Murphy, Machine Learning: A Probabilistic Perspective, MIT Press, 2012.
- Khattree, R., & Naik, D, Machine Learning Techniques for Bioinformatics In Computational Methods in Biomedical Research (pp. 57-88). Chapman and Hall/CRC, 2007.
- E. Alpaydin, Introduction to Machine Learning, MIT Press, 2014.
- C.M. Bishop, Pattern Recognition and Machine Learning, Springer, 2006.
- An introduction to machine learning theory and its applications,A visual tutorial by Nick Mccrea
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Published
2021-09-30
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Research Articles
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Copyright (c) IJSRSET
This work is licensed under a Creative Commons Attribution 4.0 International License.
How to Cite
[1]
Rajesh Yadav "A Simplistic Overview of Machine Learning" International Journal of Scientific Research in Science, Engineering and Technology (IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099,
Volume 8, Issue 5, pp.184-187, September-October-2021. Available at doi : https://doi.org/10.32628/IJSRSET218475