Bigdata and Deep Learning: Using Python Keras Predict Patient Diabetes and Employee’s Wages Per Hour
C. Rajeev1, A. Damodar2
1C. Rajeev, Department of CSE, Malla Reddy College of Engineering For Women, Maisammaguda, Dhulapally, Kompally, Medchal M, Secunderabad (Telangana), India.
2A. Damodar, Department of CSE, Malla Reddy College of Engineering For Women, Maisammaguda, Dhulapally, Kompally, Medchal M, Secunderabad (Telangana), India.
Manuscript received on 15 December 2019 | Revised Manuscript received on 22 December 2019 | Manuscript Published on 31 December 2019 | PP: 175-178 | Volume-9 Issue-1S6 December 2019 | Retrieval Number: A10351291S619/19©BEIESP | DOI: 10.35940/ijeat.A1035.1291S619
Open Access | Editorial and Publishing Policies | Cite | Mendeley | Indexing and Abstracting
© 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: In this paper we analyze big data analytic & Deep Learning is not supposing as two entire various concept. BigData mean extreme simple larger data into set in that may be analyzes as finding into pattern, trend. The first techniques in that may useful with data analyzed therefore in capable to helping to finding abstract pattern into Big Data is DeepLearning. It is applying into DeepLearning into Big Data, it can be find out nameless & useful pattern in that not possible up to now. This is technique as present into extra active areas into researches in the medical sciences. From increases sizes & complex into medical data’s such as X-ray, deeplearning gain into small success to prediction as several diseases such as pneumonia, diabetes. The project is proposed into two deeplearning model used to Keras & too we can be building in a regression models in to predicted as employee pay per hour, & we are builds in a classifications models in predict when it is na patient have been diabetes.
Keywords: Deep Learning, Big Data.
Scope of the Article: Deep Learning