Machine Learning and Deep Learning
Ayushi Chahal1, Preeti Gulia2
1Ayushi Chahal*, Department of Computer Science and Applications, Maharishi Dayanand University, Rohtak, India.
2Preeti Gulia, Department of Computer Science and Applications, Maharishi Dayanand University, Rohtak, India.
Manuscript received on September 16, 2019. | Revised Manuscript received on 24 September, 2019. | Manuscript published on October 10, 2019. | PP: 4910-4914 | Volume-8 Issue-12, October 2019. | Retrieval Number: L35501081219/2019©BEIESP | DOI: 10.35940/ijitee.L3550.1081219
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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: Now-a-days artificial intelligence has become an asset for engineering and experimental studies, just like statistics and calculus. Data science is a growing field for researchers and artificial intelligence, machine learning and deep learning are roots of it. This paper describes the relation between these roots of data science. There is a need of machine learning if any kind of analysis is to be performed. This study describes machine learning from the scratch. It also focuses on Deep Learning. Deep learning can also be known as new trend of machine learning. This paper gives a light on basic architecture of Deep learning. A comparative study of machine learning and deep learning is also given in the paper and allows researcher to have a broad view on these techniques so that they can understand which one will be preferable solution for a particular problem.
Keywords: Machine Learning, Deep learning, Artificial Intelligence, Shallow learning.
Scope of the Article: Machine Learning