Use of Machine Learning in the Pattern Finding
Uttama Garg1, Anand Kumar Shukla2, Harmanjeet Singh3, Nisha Sharma4, Sandeep Kaur5
1Uttama Garg, Assistant Professor and Research scholar , University Institute of Computing Chandigarh University, Chandigarh, India.
2Anand Kumar Shukla, Associate Professor and Research Coordinator in Chandigarh University, Mohali, Punjab, India.
3Harmanjeet Singh, Associate Professor and Research Coordinator, Chandigarh University, Mohali, Punjab, India.
4Nisha Sharma, Associate Professor and Research Coordinator, Chandigarh University, Mohali, Punjab, India.
5Er. Sandeep Kaur , Associate Professor and Research Coordinator, Chandigarh University, Mohali, Punjab, India.
Manuscript received on April 02, 2020. | Revised Manuscript received on April 16, 2020. | Manuscript published on May 30, 2020. | PP: 527-531 | Volume-9 Issue-1, May 2020. | Retrieval Number: A1237059120/2020©BEIESP | DOI: 10.35940/ijrte.A1237.059120
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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: Today is the generation of Machine Learning and Artificial Intelligence. Machine Learning is a field of scientific study and statistical models to predict the answers of never before asked questions. Machine Learning algorithms use a huge quantity of sample data that is further used to generate model. The higher amount and quality of training set lead to higher accuracy in approximate result calculation. ML is the most popular field to research and also helpful in pattern finding, artificial intelligence and data analysis. In this paper we are going to explain the basic concept of Machine Learning with its various types of methods. These methods can be used according to user’s requirement. Machine Learning tasks are divided into various categories . These tasks are accomplished by computer system without being explicitly programmed.
Keywords: Classification, clustering, regression, supervised learning.
Scope of the Article: Machine Learning